🌡️Performance Management: Critical Thinking (Definitions)

"Critical thinking is a type of thinking pattern that requires people to be reflective, and pay attention to decision-making which guides their beliefs and actions. Critical thinking allows people to deduct with more logic, to process sophisticated information and look at various sides of an issue so they can produce more solid conclusions." (Joan Baron & Robert Sternberg, "Book Reviews and Notes : Teaching Thinking Skills: Theory and Practice", 1987)

"The evaluation of ideas, sources, or solutions that are proposed as potential resources or solutions to unusual problems or to product design." (Ruth C Clark, "Building Expertise: Cognitive Methods for Training and Performance Improvement", 2008)

"Critical thinking is essentially a questioning, challenging approach to knowledge and perceived wisdom. It involves ideas and information from an objective position and then questioning this information in the light of our own values, attitudes and personal philosophy." Brenda Judge et al, "Critical Thinking Skills for Education Students", 2009)

"In academic contexts, this phrase usually refers to complex intellectual reasoning that questions assumptions and seeks to assess evidence and examine claims made by others. More simply, it can also refer to logical thinking based on facts and evidence." (Agnes Kukulska-Hulme, "Group Leadership in Online Collaborative Learning", 2009)

"Evaluation of products and ideas, such as critiquing an e-learning course or preparing an argument for a position." (Ruth C Clark & Richard E Mayer, "e-Learning and the Science of Instruction", 2011)

"Purposeful, self-regulatory judgment which results in interpretation, analysis, evaluation, and inference, as well as explanation of the evidential, conceptual, methodological, criteriological, or contextual considerations upon which that judgment is based" (Peter A Facione, "Critical Thinking: What It is and Why It Counts", 2011)

"A process in which one applies observation, analysis, inference, context, reflective thinking, and the like, in order to reach judgments. Such judgments should be open to alternative perspectives that may not normally be otherwise considered." (Project Management Institute, "Navigating Complexity: A Practice Guide", 2014)

"The ability to use your personal experience, logical thought processes, and creativity to analyze and evaluate situations. Further, critical thinking allows you to use the information gathered to reach a conclusion or answer." (Darril Gibson, "Effective Help Desk Specialist Skills", 2014)

"Thinking that is characterized by careful evaluation and judgment; this involves thinking about one’s thinking (metacognition). Critical thinking may involve examining contradictory lines of reasoning and/or using different lines of reasoning to cross-examine alternatives." (Ken Sylvester, "Negotiating in the Leadership Zone", 2015)

"Evaluation of products and ideas such as critiquing an e-learning course or preparing an argument for a position." (Ruth C Clark & Richard E Mayer, "e-Learning and the Science of Instruction", 2016)

"The capacity of an individual to effectively engage in a process of making decisions or solving problems by analyzing and evaluating evidence, arguments, claims, beliefs, and alternative points of view; synthesizing and making connections between information and arguments; interpreting information; and making inferences using reasoning appropriate to the situation." (Yigal Rosen & Maryam Mosharraf, "Evidence-Centered Concept Map in Computer-Based Assessment of Critical Thinking", 2016) 

"A set of skills that allows individuals to discriminate between essential and non-essential information and establish relationships between seemingly unconnected phenomena or ideas in the process of knowledge construction, all of which leads to deep understanding and learning." (Leonor M Martínez-Serrano, "The Pedagogical Potential of Design Thinking for CLIL Teaching: Creativity, Critical Thinking, and Deep Learning", 2020)

🕸Systems Engineering: Agent-Based Model/Modeling (Definition)

"Modeling refers to the process of designing a software representation of a real-world system or a small part of it with the purpose of replicating or simulating specific features of the modeled system. In an agent-based model, the model behavior results from behavior of many small software entities called agents. This technique is used to model real-world systems comprised of many decision-making entities with inhomogeneous preferences, knowledge, and decision-making processes. An advantage of this method is that no assumptions need to be made about an aggregate or mean behavior. Instead, this aggregation is made by the model." (E Ebenhoh, "Agent-Based Modelnig with Boundedly Rational Agents", 2007)

"A modeling and simulation approach applied to a complex system or complex adaptive system, in which the model is comprised of a large number of interacting elements (agents)." (Charles M Macal, "Agent Based Modeling and Artificial Life", 2009)

"A modeling technique with a collection of autonomous decision-making agents, each of which assesses its situation individually and makes decisions on the basis of a pre-set of rules. ABM is used to simulate land use land cover change, crowd behavior, transportation analysis and many other fine-scale geographic applications. (May Yuan, "Challenges and Critical Issues for Temporal GIS Research and Technologies", 2009)

"Agent-based models (ABM) are models where (i) there is a multitude of objects that interact with each other and with the environment; (ii) the objects are autonomous, i. e. there is no central, or top-down control over their behavior; and (iii) the outcome of their interaction is numerically computed." (Mauro Gallegati & Mateo G Richiardi, "Agent Based Models in Economics and Complexity", 2009)

"An agent-based model is a simulation made up of a set of agents and an agent interaction environment." (Michael J North & Charles M Macal, "Agent Based Modeling and Computer Languages", 2009)

"Systems composed of individuals who act purposely in making locational/spatial decisions." (Michael Batty, "Cities as Complex Systems: Scaling, Interaction, Networks, Dynamics and Urban Morphologies", 2009)

"A computational model for simulating the actions and interactions of autonomous individuals in a network, with a view to assessing their effects on the system as a whole. (Brian L. Heath & Raymond R Hill, "Agent-Based Modeling: A Historical Perspective and a Review of Validation and Verification Efforts", 2010)

"A model that involves numerous interacting autonomous agents, homogeneous or heterogeneous. The objective of agent-based modeling is to help us to understand effects and impacts of interactions of individuals." (Peter Mikulecký et al, "Possibilities of Ambient Intelligence and Smart Environments in Educational Institutions", 2011)

"a class of computational models for simulating interacting agents." (Enrico Franchi & Agostino Poggi, "Multi-Agent Systems and Social Networks", 2012)

🕸Systems Engineering: Bounded Rationality (Definitions)

"The principle of bounded rationality [is] the capacity of the human mind for formulating and solving complex problems is very small compared with the size of the problems whose solution is required for objectively rational behavior in the real world - or even for a reasonable approximation to such objective rationality." (Herbert A Simon, "Administrative Behavior", 1947)

"A decision theory that rests on the assumptions that human cognitive capabilities are limited and that these limitations are adaptive with respect to the decision environments humans frequently encounter. Decision are thought to be made usually without elaborate calculations, but instead by using fast and frugal heuristics. These heuristics certainly have the advantage of speed and simplicity, but if they are well matched to a decision environment, they can even outperform maximizing calculations with respect to accuracy. The reason for this is that many decision environments are characterized by incomplete information and noise. The information we do have is usually structured in a specific way that clever heuristics can exploit." (E Ebenhoh, "Agent-Based Modelnig with Boundedly Rational Agents", 2007)

"Bounded rationality [...] is the rationality that takes into account the limitations of the decision maker in terms of information, cognitive capacity, and attention as opposed to substantive rationality, which is not limited to satisficing, but rather aims at fully optimized solutions." (Jean-Charles Pomerol & Frédéric Adam, "Understanding the Legacy of Herbert Simon to Decision Support Systems", 2008)

"Conceptual model that assumes individuals are intentionally rational, i.e. they try to maximize their decisions. However, this ideal model is almost impossible to apply in practice: actions and decisions are taken and performed by individuals whose knowledge of the alternatives and the consequences is incomplete; in addition, preferences are subject to change and are not always clearly orderable." (Maddalena Sorrentino & Marco De Marco, "Developing an Interdisciplinary Approach to the Evaluation of E-Government Implementation", 2009)

"The assumption that agents have limited ability to acquire and process information and to solve complex economic problems. These limitations imply that expectations can diverge from RE [Rational Expectationa]." (Sebastiano Manzan, Agent Based Modeling in Finance", 2009)

"Refers to the difficulties faced by an individual in obtaining, memorizing, and processing information in an actionable manner. Although he/she may want to act rationally, the individual can only do so in a limited way, without being able to take into account all desirable information or all possible options. This limited way consists in acting on the basis of knowledge that is deemed acceptable and sufficient, rather than complete knowledge, and of simple rules, rather than a comprehensive method; and in taking shortcuts whenever possible." (Humbert Lesca & Nicolas Lesca, "Weak Signals for Strategic Intelligence: Anticipation Tool for Managers", 2011)

"The theory that personal rationality is bounded by our ability to process information, our cognitive limitations, and the finite time we have to make a decision. Although our decisions are still rational, they are rational within these constraints and, therefore, may not always appear to be rational or optimal." (Evan Stubbs, "Delivering Business Analytics: Practical Guidelines for Best Practice", 2013)

"The principle that the rationality of human beings is constrained ('bounded') by the limits of their cognition and capacity to process information." (Robert M Grant, "Contemporary Strategy Analysis" 10th Ed., 2018)

"A situation in which people have a limited capacity to anticipate, solve complex problems, or enumerate all options." (Jeffrey M Perloff & James A Brander, "Managerial Economics and Strategy" 2nd Ed., 2016)

"A concept that explains behavior that diverges from the standard assumption of a fully rational economic agent. It occurs due to limitations of cognitive ability and access to information for decision making." (Ashlesha Khedekar-Swaminathan, "Behavioral Strategies to Achieve Financial Stability in Uncertain Times", 2019)

"Bounded rationality means rationality within limits or bounds set by incomplete information, cognitive limitations of mind and limited time available for taking the decision." (Anubhuti Dwivedi, "Peace in Economic Equilibrium: A Micro-Perspective", 2019)

"Paradigm that explains agents’ strategic decision-making based on the imperfect information available to them and the expectations they have that dictate whether they will view the results as satisfactory. It leads on to the idea of adaptive learning and trial-and-error processes." (César Camisón, "Neurostrategy", 2021)

"The idea that decision making deviates from rationality due to such inherently human factors as limitations in cognitive capacity and willpower, and situational constraints." (Shaun Ruysenaar, "Thinking Critically About the Fourth Industrial Revolution as a Wicked Problem", 2021)

🕸Systems Engineering: Cellular Automata (Definitions)

"Cellular automata are mathematical models for complex natural systems containing large numbers of simple identical components with local interactions. They consist of a lattice of sites, each with a finite set of possible values. The value of the sites evolve synchronously in discrete time steps according to identical rules. The value of a particular site is determined by the previous values of a neighbourhood of sites around it." (Stephen Wolfram, "Nonlinear Phenomena, Universality and complexity in cellular automata", Physica 10D, 1984)

"A mathematical construct and technique that models a system in discrete time and discrete space in which the state of a cell depends on transition rules and the states of neighboring cells." (Charles M Macal, "Agent Based Modeling and Artificial Life", 2009) 

[Cellular automaton:] A spatially-extended dynamical system in which spatially-discrete cells take on discrete values, and evolve according to a spatially-localized discrete-time update rule." (James E Hanson, "Emergent Phenomena in Cellular Automata", 2009)

"A spatiotemporal modeling technique in which a set of rules is applied to determine the state transitions of individual cells based on each cell’s current state and the states of its neighbors." (May Yuan, "Challenges and Critical Issues for Temporal GIS Research and Technologies", 2009) 

"Cellular Automata (CA) are discrete, spatially explicit extended dynamic systems composed of adjacent cells characterized by an internal state whose value belongs to a finite set. The updating of these states is made simultaneously according to a common local transition rule involving only a neighborhood of each cell." (Ramon Alonso-Sanz, "Cellular Automata with Memory", 2009) 

"Cellular automata are dynamical systems that are discrete in space, time, and value. A state of a cellular automaton is a spatial array of discrete cells, each containing a value chosen from a finite alphabet. The state space for a cellular automaton is the set of all such configurations." (Burton Voorhees, "Additive Cellular Automata", 2009) 

"They are dynamical systems that are continuous, local, parallel, synchronous and space and time uniform. Cellular automata are used to model phenomena where the space can be regularly partitioned and where the same rules are used everywhere [...]" (Jerome Durand-Lose, "Universality of Cellular Automata", 2009)

"A discrete model consisting of a grip of cells each of which have a finite number of defined states where the state of a cells is a function of the states of neighboring cells and the transition among states is according to some predefined updating rule. (Brian L Heath & Raymond R Hill, "Agent-Based Modeling: A Historical Perspective and a Review of Validation and Verification Efforts, 2010)

"A cellular automaton is composed of a set of discrete elements - the cells - connected with other cells of the automaton, and in each time unit each cell receives information about the current state of the cells to which it is connected. The cellular automaton evolve according a transition rule that specifies the current possible states of each cell as a function of the preceding state of the cell and the states of the connected cells." (Francesc S Beltran et al, "A Language Shift Simulation Based on Cellular Automata", 2011)

"Cellular automata (CA) are idealizations of physical systems in which both space and time are assumed to be discrete and each of the interacting units can have only a finite number of discrete states." (Andreas Schadschneider et al, "Vehicular Traffic II: The Nagel–Schreckenberg Model" , 2011)

"Cellular automata (henceforth: CA) are discrete, abstract computational systems that have proved useful both as general models of complexity and as more specific representations of non-linear dynamics in a variety of scientific fields." (Francesco Berto & Jacopo Tagliabue, "Cellular Automata", Stanford Encyclopedia of Philosophy, 2012) 

🕸Systems Engineering: Bifurcation (Definitions)

"A bifurcation is an event that occurs in the evolution of a dynamic system in which the characteristic behavior of the system is transformed. This occurs when an attractor in the system changes in response to change in the value of a parameter." (Courtney Brown, "Chaos and Catastrophe Theories", 1995)

"A qualitative change in a system’s dynamics as a parameter is varied. One-parameter bifurcation diagrams often depict invariant sets of the dynamics against a single parameter, indicating stability and any bifurcation points. Two-parameter bifurcation diagrams depict curves in a parameter plane on which one-parameter bifurcations occur." (Alan Champneys, "Dynamics of Parametric Excitation", 2009) 

"A qualitative change in the essential behavior of a mathematical system (e. g., algebraic equations, iterated maps, differential equations), as a parameter is varied. Usually involves an abrupt appearance and/or disappearance of solutions." (Oded Regev, "Chaos and Complexity in Astrophysics", 2009) 

"Bifurcation is a qualitative change of the phase portrait." (George Osipenko, "Center Manifolds", 2009) 

"In parametrized dynamical systems a bifurcation occurs when a qualitative change is invoked by a change of parameters. In models such a qualitative change corresponds to transition between dynamical regimes. In the generic theory a finite list of cases is obtained, containing elements like ‘saddle-node’, ‘period doubling’, ‘Hopf bifurcation’ and many others." (Henk W Broer & Heinz Hanssmann, "Hamiltonian Perturbation Theory (and Transition to Chaos)", 2009) 

"In mathematical models, a bifurcation occurs when a small change made to a parameter value of a system causes a sudden qualitative or topological change in its behavior." (Dmitriy Laschov & Michael Margaliot, "Mathematical Modeling of the λ Switch: A Fuzzy Logic Approach", 2010)

"In dynamical systems, a bifurcation occurs when a small smooth change made to the parameter values (the bifurcation parameters) of a system causes a sudden 'qualitative' or topological change in its behaviour. Generally, at a bifurcation, the local stability properties of equilibria, periodic orbits or other invariant sets changes." (Gregory Faye, "An introduction to bifurcation theory",  2011)

"Most commonly applied to the mathematical study of dynamical systems, a bifurcation occurs when a small smooth change made to the parameter values (the bifurcation parameters) of a system causes a sudden 'qualitative' or topological change in its behavior. Bifurcations can occur in both continuous systems (described by ODEs, DDEs, or PDEs) and discrete systems (described by maps)." (Tianshou Zhou, "Bifurcation", 2013)

"Roughly speaking, refers to the phenomenon of a system exhibiting new dynamical behavior as the parameter is varied." (Wei-Bin Zhang, "Chaos in Economics", 2014)

"A sudden change that accompanies the onset of chaos at a critical value of a varied control parameter." (Viet-Thanh Pham et al, "Chaotic Attractor in a Novel Time-Delayed System with a Saturation Function", 2015) 

"A qualitative change in the behavior of a dynamic system." (Ben Tran, "Enneagram through Chaos Theory", 2016)

🔬Data Science: Fractal (Definitions)

"A fractal is a mathematical set or concrete object that is irregular or fragmented at all scales [...]" (Benoît Mandelbrot, "The Fractal Geometry of Nature", 1982)

"Objects (in particular, figures) that have the same appearance when they are seen on fine and coarse scales." (David Rincón & Sebastià Sallent, Scaling Properties of Network Traffic, 2008) "A collection of objects that have a power-law dependence of number on size." (Donald L Turcotte, "Fractals in Geology and Geophysics", 2009) 

"A fractal is a geometric object which is self-similar and characterized by an effective dimension which is not an integer." (Leonard M Sander, "Fractal Growth Processes", 2009) 

"A fractal is a structure which can be subdivided into parts, where the shape of each part is similar to that of the original structure." (Yakov M Strelniker, "Fractals and Percolation", 2009) 

"A fractal is an image that comprises two distinct attributes: infinite detail and self-similarity." (Daniel C. Doolan et al, "Unlocking the Hidden Power of the Mobile", 2009)

"A geometrical object that is invariant at any scale of magnification or reduction." (Sidney Redner, "Fractal and Multifractal Scaling of Electrical Conduction in Random Resistor Networks", 2009) 

[Fractal structure:] "A pattern or arrangement of system elements that are self-similar at different spatial scales." (Michael Batty, "Cities as Complex Systems: Scaling, Interaction, Networks, Dynamics and Urban Morphologies", 2009) 

"A set whose (suitably defined) geometrical dimensionis non-integral. Typically, the set appears selfsimilar on all scales. A number of geometrical objects associated with chaos (e. g. strange attractors) are fractals." (Oded Regev, "Chaos and Complexity in Astrophysics", 2009) 

[Fractal system:] "A system characterized by a scaling law with a fractal, i. e., non-integer exponent. Fractal systems are self-similar, i. e., a magnification of a small part is statistically equivalent to the whole." (Jan W Kantelhardt, "Fractal and Multifractal Time Series", 2009) 

"An adjective or a noun representing complex configurations having scale-free characteristics or self-similar properties. Mathematically, any fractal can be characterized by a power law distribution." (Misako Takayasu & Hideki Takayasu, "Fractals and Economics", 2009) 

"Fractals are complex mathematical objects that are invariant with respect to dilations (self-similarity) and therefore do not possess a characteristic length scale. Fractal objects display scale-invariance properties that can either fluctuate from point to point (multifractal) or be homogeneous (monofractal). Mathematically, these properties should hold over all scales. However, in the real world, there are necessarily lower and upper bounds over which self-similarity applies." (Alain Arneodo et al, "Fractals and Wavelets: What Can We Learn on Transcription and Replication from Wavelet-Based Multifractal Analysis of DNA Sequences?", 2009) 

"Mathematical object usually having a geometrical representation and whose spatial dimension is not an integer. The relation between the size of the object and its “mass” does not obey that of usual geometrical objects." (Bastien Chopard, "Cellular Automata: Modeling of Physical Systems", 2009) 

 "A fragmented geometric shape that can be split up into secondary pieces, each of which is approximately a smaller replica of the whole, the phenomenon commonly known as self similarity." (Khondekar et al, "Soft Computing Based Statistical Time Series Analysis, Characterization of Chaos Theory, and Theory of Fractals", 2013) 

 "A natural phenomenon or a mathematical set that exhibits a repeating pattern which can be replicated at every scale." (Rohnn B Sanderson, "Understanding Chaos as an Indicator of Economic Stability", 2016) 

 "Geometric pattern repeated at progressively smaller scales, where each iteration is about a reproduction of the image to produce completely irregular shapes and surfaces that can not be represented by classical geometry. Fractals are generally self-similar (each section looks at all) and are not subordinated to a specific scale. They are used especially in the digital modeling of irregular patterns and structures in nature." (Mauro Chiarella, Folds and Refolds: Space Generation, Shapes, and Complex Components, 2016)

🕸Systems Engineering: Chaos (Definitions)

"Long-term unpredictable behaviour caused by sensitive dependence on initial conditions." (Jesús B A Hernández & Patricia H Rodríguez, "Nonlinear Techniques for Signals Characterization", 2009)

"The effect whereby minor deficiencies or miniscule changes occurring in any phase of the project, but particularly in the beginning of a process, create significantly different outcomes." (José L Fernández-Solís & Iván Mutis, "The Idealization of an Integrated BIM, Lean, and Green Model (BLG)", 2010)

"A situation where a complex and random-looking behavior arises from simple nonlinear deterministic systems with sensitive dependence on initial conditions." (Bellie Sivakumar, "Chaos Theory for Hydrologic Modeling and Forecasting: Progress and Challenges", 2011)

"An interesting deterministic experience which has a random and unpredictable apparent behavior where petite changes in the initial conditions can lead to immense changes over time." (Mofazzal H. Khondekar et al, "Soft Computing Based Statistical Time Series Analysis, Characterization of Chaos Theory, and Theory of Fractals", 2013)

"A nonlinear erratic phenomenon that is found to be exhibited in several physical systems." (Hassène Gritli, "Further Investigation of the Period-Three Route to Chaos in the Passive Compass-Gait Biped Model", 2015)

"A type of behavior of a deterministic nonlinear system, where tiny changes in initial conditions make huge changes over time." (Viet-Thanh Pham et al, "Chaotic Attractor in a Novel Time-Delayed System with a Saturation Function", 2015)

"The type of behavior of a complex system, where tiny changes in a system’s initial conditions can lead to very large changes over time." (Christos Volos, "Random Bit Generator Based on Non-Autonomous Chaotic Systems", 2015)

"A state of disorder where each unit of a system behaves independently from each other at the same point of time." (Simanti Bhattacharya & Angshuman Bagchi, "Cellular Automata-Basics: Applications in Problem Solving", 2016)

"A new branch of science that deals with systems whose evolution depends very sensitively upon the initial conditions." (Wassim J Aloulou, "Understanding Entrepreneurship through Chaos and Complexity Perspectives", 2016)

🕸Systems Engineering: Systems Engineering (Just the Quotes)

"The engineer must be able not only to design, but to execute. A draftsman may be able to design, but unless he is able to execute his designs to successful operation he cannot be classed as an engineer. The production engineer must be able to execute his work as he has planned it. This requires two qualifications in addition to technical engineering ability: He must know men, and he must have creative ability in applying good statistical, accounting, and 'system' methods to any particular production work he may undertake." (Hugo Diemer, "Industrial Engineering", 1905)

"The analysis of engineering systems and the understanding of economic structure have advanced since then, and the time is now more ripe to bring these topics into a potentially fruitful marriage." (Arnold Tustin, "The Mechanism of Economic Systems", 1953)

"The term 'systems engineering' is a term with an air of romance and of mystery. The romance and the mystery come from its use in the field of guided missiles, rockets, artificial satellites, and space flight. Much of the work being done in these areas is classified and hence much of it is not known to the general public or to this writer. […] From a business point of view, systems engineering is the creation of a deliberate combination of human services, material services, and machine service to accomplish an information processing job. But this is also very nearly a definition of business system analysis. The difference, from a business point of view, therefore, between business system analysis and systems engineering is only one of degree. In general, systems engineering is more total and more goal-oriented in its approach [...]." ("Computers and People" Vol. 5, 1956)

"By some definitions 'systems engineering' is suggested to be a new discovery. Actually it is a common engineering approach which has taken on a new and important meaning because of the greater complexity and scope of problems to be solved in industry, business, and the military. Newly discovered scientific phenomena, new machines and equipment, greater speed of communications, increased production capacity, the demand for control over ever-extending areas under constantly changing conditions, and the resultant complex interactions, all have created a tremendously accelerating need for improved systems engineering. Systems engineering can be complex, but is simply defined as 'logical engineering within physical, economic and technical limits' - bridging the gap from fundamental laws to a practical operating system." (Instrumentation Technology, 1957)

"Systems engineering embraces every scientific and technical concept known, including economics, management, operations, maintenance, etc. It is the job of integrating an entire problem or problem to arrive at one overall answer, and the breaking down of this answer into defined units which are selected to function compatibly to achieve the specified objectives. [...] Instrument and control engineering is but one aspect of systems engineering - a vitally important and highly publicized aspect, because the ability to create automatic controls within overall systems has made it possible to achieve objectives never before attainable, While automatic controls are vital to systems which are to be controlled, every aspect of a system is essential. Systems engineering is unbiased, it demands only what is logically required. Control engineers have been the leaders in pulling together a systems approach in the various technologies." (Instrumentation Technology, 1957) 

"Systems engineering is more likely to be closely associated with top management of an enterprise than the engineering of the components of the system. If an engineering task is large and complex enough, the arrangement-making problem is especially difficult. Commonly, in a large job, the first and foremost problem for the systems engineers is to relate the objectives to the technical art. [...] Systems engineering is a highly technical pursuit and if a nontechnical man attempts to direct the systems engineering as such, it must end up in a waste of technical talent below." (Aeronautical Engineering Review Vol. 16, 1957) 

"Systems engineering is the name given to engineering activity which considers the overall behavior of a system, or more generally which considers all factors bearing on a problem, and the systems approach to control engineering problems is correspondingly that approach which examines the total dynamic behavior of an integrated system. It is concerned more with quality of performance than with sizes, capacities, or efficiencies, although in the most general sense systems engineering is concerned with overall, comprehensive appraisal." (Ernest F Johnson, "Automatic process control", 1958)

"There are two types of systems engineering - basis and applied. [...] Systems engineering is, obviously, the engineering of a system. It usually, but not always, includes dynamic analysis, mathematical models, simulation, linear programming, data logging, computing, optimating, etc., etc. It connotes an optimum method, realized by modern engineering techniques. Basic systems engineering includes not only the control system but also all equipments within the system, including all host equipments for the control system. Applications engineering is - and always has been - all the engineering required to apply the hardware of a hardware manufacturer to the needs of the customer. Such applications engineering may include, and always has included where needed, dynamic analysis, mathematical models, simulation, linear programming, data logging, computing, and any technique needed to meet the end purpose - the fitting of an existing line of production hardware to a customer's needs. This is applied systems engineering." (Instruments and Control Systems Vol. 31, 1958)

"In a society which is producing more people, more materials, more things, and more information than ever before, systems engineering is indispensable in meeting the challenge of complexity." (Harold Chestnut, "Systems Engineering Tools," 1965)

"Systems engineering is most effectively conceived of as a process that starts with the detection of a problem and continues through problem definition, planning and designing of a system, manufacturing or other implementing section, its use, and finally on to its obsolescence. Further, Systems engineering is not a matter of tools alone; It is a careful coordination of process, tools and people." (Arthur D. Hall, "Systems Engineering from an Engineering Viewpoint" In: Systems Science and Cybernetics. Vol.1 Issue.1, 1965)

"Systems Engineering Methods is directed towards the development of a broad systems engineering approach to help such people improve their decision-making capability. Although the emphasis is on engineering, the systems approach can also has validity for many other areas in which emphasis may be social, economic, or political." (Harold Chestnut, "Systems Engineering Methods", 1965) 

"The Systems engineering method recognizes each system is an integrated whole even though composed of diverse, specialized structures and sub-functions. It further recognizes that any system has a number of objectives and that the balance between them may differ widely from system to system. The methods seek to optimize the overall system functions according to the weighted objectives and to achieve maximum compatibility of its parts." (Harold Chestnut, "Systems Engineering Tools," 1965)

"In the minds of many writers systems engineering is synonymous with component selection and interface design; that is, the systems engineer does not design hardware but decides what types of existing hardware shall be coupled and how they shall be coupled. Complete agreement that this function is the essence of systems engineering will not be found here, for, besides the very important function of systems engineering in systems analysis, there is the role played by systems engineering in providing boundary conditions for hardware design." (A Wayne Wymore, "A Mathematical Theory of Systems Engineering", 1967)

"Only if mathematical rigor is adhered to, can systems problems be dealt with effectively, and so it is that the systems engineer must, at least, develop an appreciation for mathematical rigor if not also considerable mathematical competence." (A Wayne Wymore, "A Mathematical Theory of Systems Engineering", 1967)

"Systems Engineering is the science of designing complex systems in their totality to ensure that the component sub-systems making up the system are designed, fitted together, checked and operated in the most efficient way." (Gwilym Jenkins, "The Systems Approach", 1969) 

"The purpose and real value of systems engineering is [...] to keep going around the loop; find inadequacies and make improvements." (Robert E Machol, "Mathematicians are useful", 1971)

"System engineering is a robust approach to the design, creation, and operation of systems. In simple terms, the approach consists of identification and quantification of system goals, creation of alternative system design concepts, performance of design trades, selection and implementation of the best design, verification that the design is properly built and integrated, and post-implementation assessment of how well the system meets (or met) the goals." (NASA, "NASA Systems Engineering Handbook", 1995) 

"System engineering is the art and science of creating effective systems, using whole system, whole life principles." (Derek Hitchins, 1995)

"With the subsequent strong support from cybernetics, the concepts of systems thinking and systems theory became integral parts of the established scientific language, and led to numerous new methodologies and applications - systems engineering, systems analysis, systems dynamics, and so on." (Fritjof Capra, "The Web of Life", 1996)

"Systems engineering differs from traditional disciplines in that (1) it is focused on the system as a whole; (2) it is concerned with customer needs and operational environment; (3) it leads system conceptual design; and (4) it bridges traditional engineering disciplines and gaps between specialties. Moreover, systems engineering is an integral part of project management in that it plans and guides the engineering effort." (Alexander Kossiakoff et al, "Systems Engineering: Principles and practice" 2nd Ed., 2003)

"Systems engineering is an inherent part of project management - the part that is concerned with guiding the engineering effort itself - setting its objectives, guiding its execution, evaluating its results, and prescribing necessary corrective actions to keep it on course." (Alexander Kossiakoff et al, "Systems Engineering: Principles and practice" 2nd Ed., 2003)

"Systems engineering is focused on the system as a whole; it emphasizes its total operation. It looks at the system from the outside, that is, at its interactions with other systems and the environment, as well as from the inside. It is concerned not only with the engineering design of the system but also with external factors, which can significantly constrain the design." (Alexander Kossiakoff et al, "Systems Engineering: Principles and practice" 2nd Ed., 2003)

"It is no longer sufficient for engineers merely to design boxes such as computers with the expectation that they would become components of larger, more complex systems. That is wasteful because frequently the box component is a bad fit in the system and has to be redesigned or worse, can lead to system failure. We must learn how to design large-scale, complex systems from the top down so that the specification for each component is derivable from the requirements for the overall system. We must also take a much larger view of systems. We must design the man-machine interfaces and even the system-society interfaces. Systems engineers must be trained for the design of large-scale, complex, man-machine-social systems." (A Wayne Wymore, "Systems Movement: Autobiographical Retrospectives", 2004)

"The basic idea of systems engineering is that it is possible to take a large and highly complex system that one wants to build, separate it into key parts, give the parts to different groups of people to work on, and coordinate their development so that they can be put together at the end of the process. This mechanism is designed to be applied recursively, so that we separate the large system into parts, then the parts into smaller parts, until each part is small enough for one person to execute. Then we put all of the parts together until the entire system works." (Yaneer Bar-Yam, "Making Things Work: Solving Complex Problems in a Complex World", 2004)

"Systems engineering should be, first and foremost, a state of mind and an attitude taken when dealing with complexity." (Dominique Luzeaux et al, "Complex Systems and Systems of Systems Engineering", 2013) 

"The central activity of engineering, as distinguished from science, is the design of new devices, processes and systems." (Myron Tribus, "Rational Descriptions, Decisions and Designs", 2016)

"Over-engineering is a real disease of many engineers as they delight in design purity and ignore tradeoffs." (Alex Xu, "System Design Interview: An insider's guide", 2017)

"If all the theories pertinent to systems engineering could be discussed within a common framework by means of a standard set of nomenclature and definitions, many separate courses might not be required." (A Wayne Wymore)

🕸Systems Engineering: Resilience (Definitions)

"The ability of a system, community, or society exposed to hazards to resist, absorb, accommodate to and recover from the effects of a hazard in a timely and efficient manner, including through the preservation and restoration of its essential basic structures and functions." (ISDR, 2009)

"The quality of being able to absorb systemic 'shocks' without being destroyed even if recovery produces an altered state to that of the status quo ante." (Philip Cooke, "Regional Innovation Systems in Centralised States: Challenges, Chances, and Crossovers", 2015)

"A swarm is resilient if the loss of individual agents has little impact on the success of the task of the swarm." (Thalia M Laing et al, "Security in Swarm Robotics", 2016)

"Resilience is the capacity of organism or system to withstand stress and catastrophe." (Sunil L Londhe, "Climate Change and Agriculture: Impacts, Adoption, and Mitigation", 2016)

"System resilience is an ability of the system to withstand a major disruption within acceptable degradation parameters and to recover within an acceptable time." (Denis Čaleta, "Cyber Threats to Critical Infrastructure Protection: Public Private Aspects of Resilience", 2016) 

"The capacity for self-organization, and to adapt to impact factors." (Ahmed Karmaoui, Environmental Vulnerability to Climate Change in Mediterranean Basin: Socio-Ecological Interactions between North and South, 2016)

"The capacity of ecosystem to absorb disturbance, reorganize and return to an equilibrium or steady-state while undergoing some change or perturbation so that still retain essentially the same function, structure, identity, and feedbacks." (Susmita Lahiri et al, "Role of Microbes in Eco-Remediation of Perturbed Aquatic Ecosystem", 2017)

"A capability to anticipate, prepare for, respond to, and recover from significant multi-hazard threats with minimum damage to social well-being, the economy, and the environment." (Carolyn N Stevenson, "Addressing the Sustainable Development Goals Through Environmental Education", 2019)

"The conventional understanding of resilience applied to socioeconomic studies regards the bouncing-back ability of a socioeconomic system to recover from a shock or disruption. Today resilience is being influenced by an evolutionary perspective, underlining it as the bouncing-forward ability of the system to undergo anticipatory or reactionary reorganization to minimize the impact of destabilizing shocks and create new growth trajectories." (Hugo Pinto & André Guerreiro, "Resilience, Innovation, and Knowledge Transfer: Conceptual Considerations and Future Research Directions", 2019)

"Is the system capacity to rebalance after a perturbation." (Ahmed Karmaoui et al, "Composite Indicators as Decision Support Method for Flood Analysis: Flood Vulnerability Index Category", 2020)

"The ability of human or natural systems to cope with adverse events and be able to effect a quick recovery." (Maria F Casado-Claro, "Fostering Resilience by Empowering Entrepreneurs and Small Businesses in Local Communities in Post-Disaster Scenarios", 2021)

"The word resilience refers to the ability to overcome critical moments and adapt after experiencing some unusual and unexpected situation. It also indicates return to normal." (José G Vargas-Hernández, "Urban Socio-Ecosystems Green Resilience", 2021)

🕸Systems Engineering: Systems Thinking (Definitions)

"Systems thinking is a discipline for seeing the 'structures' that underlie complex situations, and for discerning high from low leverage change. That is, by seeing wholes we learn how to foster health. To do so, systems thinking offers a language that begins by restructuring how we think." (Peter Senge, "The Fifth Discipline", 1990)

"Systems thinking is a framework for seeing interrelationships rather than things, for seeing patterns rather than static snapshots. It is a set of general principles spanning fields as diverse as physical and social sciences, engineering and management." (Peter Senge, "The Fifth Discipline", 1990)

"A school of thought that focuses on recognizing the interconnections between the parts of a system and synthesizing them into a unified view of the whole." (Virginia Anderson & Lauren Johnson, "Systems Thinking Basics: From Concepts to Casual Loops", 1997)

"Systems thinking means the ability to see the synergy of the whole rather than just the separate elements of a system and to learn to reinforce or change whole system patterns." (Richard L Daft, "The Leadership Experience", 2002)

"A concept for describing a way of helping people view systems from a wide perspective, seeing overall structures, patterns and cycles in subsystems, rather than seeing only specific events in the main system." (Thomas Hansson, "Communication and Relation Building in Social Systems", 2008)

"Systems thinking is a mental discipline and framework for seeing patterns and interrelationships." (Richard L Daft, "The Leadership Experience", 2008) 

"A manner of thinking that takes into account how the things being studied relate and connect to each other. A key idea embedded in systems theory is that it can assist us in understanding of phenomena and that its holistic emphasis will promote orderly thinking. It is an apt approach to use when thinking about complex issues and interactions." (Deborah W Proctor, "Accessibility of Technology in Higher Education", 2009)

"An approach to analysis, based on the insight that components of a system or (sub)systems may act differently when isolated from the interacting environment and hence the basic concept for studying systems in a holistic way as a supplement to traditional reductionistic techniques." (Herwig Ostermann et al, "Benchmarking Human Resource Information Systems", 2009)

"Critical to this definition is the term ‘interaction’, in that systems thinking is a form of analysis that goes beyond specific causes and effects to the discernment of hidden patterns of behaviors and underlying systemic interrelationships." (Gerald Goodman & Anne Selcer, "Systems Thinking as the Model for Educating Future Healthcare Managers in Information Technology", 2009)

"Is thinking holistically and conscientiously about the world by focusing on the interaction of the parts and their influence within and over the system." (Kambiz E Maani, "Systems Thinking and the Internet from Independence to Interdependence", 2009)

"A holistic concept of tackling problems and events by taking into account the larger scope in the complete environment." (Nashon J Adero et al, "Flow-Based Structural Modelling and Dynamic Simulation of Lake Water Levels", 2011)

"An approach that emphasizes the interconnected nature of the different components that make up a system. Thus, to understand a problem with performance in an organization, you must analyze the whole organizational system not just the component (process, unit or individual) that on the surface seems to be the root of the problem." (Ian Douglas, "Organizational Needs Analysis and Knowledge Management", 2011)

"An approach to understanding the interconnectedness of components when grouped together in order to solve a problem and how the grouped components behave under different stimuli." (Kyle G. Gipson & Robert J Prins, "Materials and Mechanics: A Multidisciplinary Course Incorporating Experiential, Project/Problem-Based, and Work-Integrated Learning Approaches for Undergraduates", 2015)

"In a system dynamics context, a way of thinking based on system dynamics. It is also used to mean system dynamics analyses without quantitative definitions. It focuses on feedback loop structure in order to forecast the direction of performance and find pertinent elements for controlling systems. This is also called qualitative system dynamics." (Yutaka Takahashi, "System Dynamics", 2015)

"Systems thinking is a discipline or process that considers how individual elements interact with one another as part of a whole entity. As an approach to solving problems, systems thinking uses relationships among individual elements and the dynamics of these relationships to explain the behavior of systems such as an ecosystem, social system, or organization." (Karen L Higgins, "Economic Growth and Sustainability: Systems Thinking for a Complex World", 2015)

"The process and understanding of how items influence one another within a whole." (Reginald Wilson, "Outage Analysis and Maintenance Strategies in Hydroelectric Production", 2015)

"A perspective and approach to problem-solving that emphasizes understanding the world in terms of dynamic systems, the interrelationships among elements of systems, and how systems influence each other." (Elisabeth R Gee Kelly M Tran, "Video Game Making and Modding", 2016)

"A relevant scientific instrumentarium, based on principles of General Systems Theory, which uses the systems ideas in order to research and solve complex strategic problems/problem situations." (Dejana Zlatanović et al, "Higher Education Institutions as Viable Systems: A Cybernetic Framework for Innovativeness", 2020)

"The process of understanding how things influence one another. It refers rather to seeing overall structures, patterns and cycles in systems, and the connections between them, than specific events in the system." (The KPI Institute)

🕸Systems Engineering: System Dynamics (Definitions)

"A field of study that includes a methodology for constructing computer simulation models to achieve better under-standing of social and corporate systems. It draws on organizational studies, behavioral decision theory, and engineering to provide a theoretical and empirical base for structuring the relationships in complex systems." (Virginia Anderson & Lauren Johnson, "Systems Thinking Basics: From Concepts to Casual Loops", 1997) 

"A methodology for studying and managing complex feedback systems, such as one finds in business and other social systems." (Lars O Petersen, "Balancing the Capacity in Health Care", 2008)

"System dynamics is a top-down approach for modelling system changes over time. Key state variables that define the behaviour of the system have to be identified and these are then related to each other through coupled, differential equations." (Peer-Olaf Siebers & Uwe Aickelin, "Introduction to Multi-Agent Simulation", 2008) 

"A continuous simulation of systems exhibiting feedback loops. The feedbacks can either intensify activities of the system (positive feedback) or slow them down and stabilize the system (negative feedback)." (Nikola Vlahovic & Vlatko Ceric, "Multi-Agent Simulation in Organizations: An Overview", 2009)

"Is a scientific tool which embodies principles from biology, ecology, psychology, mathematics, and computer science to model complex and dynamic systems." (Kambiz E Maani, "Systems Thinking and the Internet from Independence to Interdependence", 2009)

"System dynamics is an approach to understanding the behaviour of over time. It deals with internal feedback loops and time delays that affect the behaviour of the entire system. It also helps the decision maker untangle the complexity of the connections between various policy variables by providing a new language and set of tools to describe. Then it does this by modeling the cause and effect relationships among these variables." (Raed M Al-Qirem & Saad G Yaseen, "Modelling a Small Firm in Jordan Using System Dynamics", 2010)

[system dynamics simulation:] "A dynamic form of visualization that combines causal loop diagrams and stock and flow diagrams to create a simulation of the workings of a system from one point in time to another." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"An approach for capturing the complex inter- and intra- dependencies that characterize systems, including feedback over time." (Howard Passell, "Collaborative, Stakeholder-Driven Resource Modeling and Management", 2011)

This studies the non-linear interaction of systems of many connected equations. The approach is based on differential equations. It describes the dynamical properties of a whole system using internal negative and positive feedback loops as well as the use of stocks and flows. (Martin Neumann, "An Epistemological Gap in Simulation Technologies and the Science of Society", 2011)

"A simulation-modelling approach to understand the structure and behaviour of complex dynamic systems over time." (Jaime A Palma-Mendoza, "Hybrid SD/DES Simulation for Supply Chain Analysis", 2014)

"A systems simulation methodology to study complex dynamic behavior of industrial and social systems based on control engineering and cybernetics." (Michael Mutingi & Charles Mbohwa, 2014)

[system dynamics:] "The interactions of connected and interdependent components, which may cause change over time and give rise to interconnected risks; emerging, unforeseeable issues; and unclear, disproportional cause-and-effect relationships." (Project Management Institute, "Navigating Complexity: A Practice Guide", 2014)

"A continuous simulation of systems exhibiting feedback loops. The feedbacks can either intensify activities of the system (positive feedback) or slow them down and stabilize the system (negative feedback)." (Nikola Vlahovic & Vlatko Ceric, "An Overview of Multi-Agent Simulation in Organizations", 2015)

"System Dynamics is a dynamic modelling approach at system level which is primarily used to understand interconnected systems and their evolution over time. Basic elements to represent the systems are internal feedback loops as well as stocks and flows." (Catalina Spataru et al, "Multi-Scale, Multi-Dimensional Modelling of Future Energy Systems", 2015)

"System dynamics [...] uses models and computer simulations to understand behavior of an entire system, and has been applied to the behavior of large and complex national issues. It portrays the relationships in systems as feedback loops, lags, and other descriptors to explain dynamics, that is, how a system behaves over time. Its quantitative methodology relies on what are called 'stock-and-flow diagrams' that reflect how levels of specific elements accumulate over time and the rate at which they change. Qualitative systems thinking constructs evolved from this quantitative discipline." (Karen L Higgins, "Economic Growth and Sustainability: Systems Thinking for a Complex World", 2015)

"A simulation technique based on the solution of differential equations, in which the status variables of a system vary with continuity." (Lorenzo Damiani et al, "Different Approaches for Studying Interruptible Industrial Processes: Application of Two Different Simulation Techniques", 2016)

"A technique que allow to obtain models to explore possible futures or scenarios and ask 'what if' questions in complex situations." (Ruth R Gallegos, "Using Modeling and Simulation to Learn Mathematics", Handbook of Research on Driving STEM Learning With Educational Technologies, 2017)

"A method through which the dynamic behaviour of a complex system over time can be better understood by taking into account internal feedback and time delays." (Henry Xu & Renae Agrey, "Major Techniques and Current Developments of Supply Chain Process Modelling", 2018)

"Computer-aided methodology able to represent the causal structure of a system through stock-and-flow feedback structures and computer simulations regarding the accumulation of materials, information, people, and money." (Francesca Costanza, "Governing Patients' Mobility to Pursue Public Value: A System Dynamic Approach to Improve Healthcare Performance Management", 2018)

"The basis of system dynamics is to understand how system structures cause system behavior and system events." (Arzu E Şenaras, "A Suggestion for Energy Policy Planning System Dynamics", 2018)

🕸Systems Engineering: Systems Theory (Just the Quotes)

"Linking the basic parts are communication, balance or system parts maintained in harmonious relationship with each other and decision making. The system theory include both man-machine and interpersonal relationships. Goals, man, machine, method, and process are woven together into a dynamic unity which reacts." (George R Terry, "Principles of Management", 1960)

"Industrial production, the flow of resources in the economy, the exertion of military effort in a war theater-all are complexes of numerous interrelated activities. Differences may exist in the goals to be achieved, the particular processes involved, and the magnitude of effort. Nevertheless, it is possible to abstract the underlying essential similarities in the management of these seemingly disparate systems." (George Dantzig, "Linear programming and extensions", 1963) 

"The aim of systems theory for business is to develop an objective, understandable environment for decision making; that is, if the system within which managers make the decisions can be provided as an explicit framework, then such decision making should be easier to handle." (Richard A Johnson et al, "Systems Theory and Management", Management Science Vol. 10 (2), 1964)

"System theory is basically concerned with problems of relationships, of structure, and of interdependence rather than with the constant attributes of objects. In general approach it resembles field theory except that its dynamics deal with temporal as well as spatial patterns. Older formulations of system constructs dealt with the closed systems of the physical sciences, in which relatively self-contained structures could be treated successfully as if they were independent of external forces. But living systems, whether biological organisms or social organizations, are acutely dependent on their external environment and so must be conceived of as open systems." (Daniel Katz, "The Social Psychology of Organizations", 1966)

"Clearly, if it is possible to have a self-regulating system that implicitly arranges its own stability, then this is of the keenest management interest." (Anthony S Beer, "Management Science", 1968) 

"The management of a system has to deal with the generation of the plans for the system, i. e., consideration of all of the things we have discussed, the overall goals, the environment, the utilization of resources and the components. The management sets the component goals, allocates the resources, and controls the system performance." (C West Churchman, "The Systems Approach", 1968)

"Perhaps the most important single characteristic of modern organizational cybernetics is this: That in addition to concern with the deleterious impacts of rigidly-imposed notions of what constitutes the application of good 'principles of organization and management' the organization is viewed as a subsystem of a larger system(s), and as comprised itself of functionally interdependent subsystems." (Richard F Ericson, "Organizational cybernetics and human values", 1969) 

"Organizationally what is required - and evolving - is systems management." (Peter Drucker, "MANAGEMENT: Tasks, Responsibilities, Practices", 1973)

"The subject of study in systems theory is not a 'physical object', a chemical or social phenomenon, for example, but a 'system': a formal relationship between observed features or attributes. For conceptual reasons, the language used in describing the behavior of systems is that of information processing and goal seeking (decision making control)." (Mihajlo D Mesarovic & Y Takahara, "Foundations for the mathematical theory of general systems", 1975)

"Systems theory looks at the world in terms of the interrelatedness and interdependence of all phenomena, and in this framework an integrated whole whose properties cannot be reduced to those of its parts is called a system. Living organisms, societies, and ecosystems are all systems." (Fritjof Capra, "The Turning Point: Science, Society, and the Turning Culture", 1982)

"The supposition is prevalent the world over that there would be no problems in production or service if only our production workers would do their jobs in the way that they we taught. Pleasant dreams. The workers are handicapped by the system, and the system belongs to the management." (W Edwards Deming, "Out Of The Crisis", 1982)

"A cardinal principle in systems theory is that all parties that have a stake in a system should be represented in its management." (Malcolm Knowles, "The Adult Learner: A Neglected Species", 1984)

"A manager of people needs to understand that all people are different. This is not ranking people. He needs to understand that the performance of anyone is governed largely by the system that he works in, the responsibility of management." (W Edwards Deming, "The New Economics: For Industry, Government, Education", 1993)

"The prevailing style of management must undergo transformation. A system can not understand itself. The transformation requires a view from outside." (W Edwards Deming, "The New Economics: For Industry, Government, Education", 1993)

More quotes on "Systems Theory" at the-web-of-knowledge.blogspot.com. 

🕸Systems Engineering: Entropy (Definitions)

"The Entropy of a system is the mechanical work it can perform without communication of heat, or alteration of its total volume, all transference of heat being performed by reversible engines." (James C Maxwell, "Theory of Heat", 1899)

"Entropy is the measure of randomness." (Lincoln Barnett, "The Universe and Dr. Einstein", 1948)

"Entropy is a measure of the heat energy in a substance that has been lost and is no longer available for work. It is a measure of the deterioration of a system." (William B. Sill & Norman Hoss (Eds.), "Popular Science Encyclopedia of the Sciences", 1963)

"Entropy [...] is the amount of disorder or randomness present in any system." (Lars Skyttner, "General Systems Theory: Ideas and Applications", 2001)

"A measurement of the disorder of a data set." (Glenn J Myatt, "Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining", 2006)

"[...] entropy is the amount of hidden microscopic information." (Leonard Susskind, "The Black Hole War", 2008)

"A measure of the uncertainty associated with a random variable. Entropy quantifies information in a piece of data." (Radu Mutihac, "Bayesian Neural Networks for Image Restoration" [in "Encyclopedia of Artificial Intelligence", 2009)

"Measurement that can be used in machine learning on a set of data that is to be classified. In this setting it can be defined as the amount of uncertainty or randomness (or noise) in the data. If all data is classified with the same class, the entropy of that set would be 0." (Isak Taksa et al, "Machine Learning Approach to Search Query Classification", 2009)

"A measure of uncertainty associated with the predictable value of information content. The highest information entropy is when the ambiguity or uncertainty of the outcome is the greatest." (Alex Berson & Lawrence Dubov, "Master Data Management and Data Governance", 2010)

"Refers to the inherent unknowability of data to external observers. If a bit is just as likely to be a 1 as a 0 and a user does not know which it is, then the bit contains 1 bit of entropy." (Mark S Merkow & Lakshmikanth Raghavan, "Secure and Resilient Software Development", 2010)

"The measurement of uncertainty in an outcome, or randomness in a system." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A metric used to evaluate and describe the amount of randomness associated with a random variable."(Wenbing Zhao, "Increasing the Trustworthiness of Online Gaming Applications", 2015)

"Anti-entropy is the process of detecting differences in replicas. From a performance perspective, it is important to detect and resolve inconsistencies with a minimum amount of data exchange." (Dan Sullivan, "NoSQL for Mere Mortals®", 2015)

"Average amount of information contained in a sample drawn from a distribution or data stream. Measure of uncertainty of the source of information." (Anwesha Sengupta et al, "Alertness Monitoring System for Vehicle Drivers using Physiological Signals", 2016)

"In information theory this notion, introduced by Claude Shannon, is used to express unpredictability of information content. For instance, if a data set containing n items was divided into k groups each comprising n i items, then the entropy of such a partition is H = p 1 log( p 1 ) + … + p k log( p k ), where p i = n i / n . In case of two alternative partitions, the mutual information is a measure of the mutual dependence between these partitions." (Slawomir T Wierzchon, "Ensemble Clustering Data Mining and Databases", 2018) [where i is used as index]

"Entropy is a measure of amount of uncertainty or disorder present in the system within the possible probability distribution." ("G Suseela & Y Asnath V Phamila, "Security Framework for Smart Visual Sensor Networks", 2019)

"Lack of order or predictability; gradual decline into disorder." (Adrian Carballal et al, "Approach to Minimize Bias on Aesthetic Image Datasets", 2019)

"It is the quantity which is used to describe the amount of information which must be coded for compression algorithm." (Arockia Sukanya & Kamalanand Krishnamurthy, "Thresholding Techniques for Dental Radiographic Images: A Comparative Study", 2019)

"In the physics - rate of system´s messiness or disorder in a physical system. In the social systems theory - social entropy is a sociological theory that evaluates social behaviors using a method based on the second law of thermodynamics." (Justína Mikulášková et al, "Spiral Management: New Concept of the Social Systems Management", 2020)

🕸Systems Engineering: Cybernetics (Definitions)

"Cybernetics […] combines under one heading the study of what in a human context is sometimes loosely described as thinking and in engineering is known as control and communication. In other words, cybernetics attempts to find the common elements in the functioning of automatic machines and of the human nervous system, and to develop a theory which will cover the entire field of control and communication in machines and in living organisms." (Norbert Wiener, "Cybernetics", 1948)

The 'cybernetics' of Wiener […] is the science of organization of mechanical and electrical components for stability and purposeful actions." (Qian Xuesen, "Engineering Cybernetics", 1954) 

"[Cybernetics is] the art of ensuring the efficacy of action." (Louis Couffignal, 1958)

"Cybernetics is the science of the process of transmission, processing and storage of information." (Sergei Sobolew, Woprosy Psychology, 1958)

"Cybernetics is the general science of communication. But to refer to communication is consciously or otherwise to refer to distinguishable states of information inputs and outputs and /or to information being processed within some relatively isolated system." (Henryk Greniewski, "Cybernetics without Mathematics", 1960)

"Cybernetics is the science or the art of manipulating defensible metaphors; showing how they may be constructed and what can be inferred as a result of their existence." (Gordon Pask, "The Cybernetics of Human Performance and Learning", 1966)

"Cybernetics is concerned with scientific investigation of systemic processes of a highly varied nature, including such phenomena as regulation, information processing, information storage, adaptation, self-organization, self-reproduction, and strategic behavior. Within the general cybernetic approach, the following theoretical fields have developed: systems theory (system), communication theory, game theory, and decision theory." (Fritz B Simon et al, "Language of Family Therapy: A Systemic Vocabulary and Source Book", 1985)

"Cybernetics is the science of effective organization, of control and communication in animals and machines. It is the art of steersmanship, of regulation and stability. The concern here is with function, not construction, in providing regular and reproducible behaviour in the presence of disturbances." (Chris Lucas, "Cybernetics and Stochastic Systems", 1999)

"Cybernetics is the study of systems and processes that interact with themselves and produce themselves from themselves." (Louis Kauffman, 2007)

"Cybernetics is the art of creating equilibrium in a world of possibilities and constraints." (Ernst von Glasersfeld, "Partial Memories: Sketches from an Improbable Life", 2010)

"Cybernetics is the study of systems which can be mapped using loops (or more complicated looping structures) in the network defining the flow of information. Systems of automatic control will of necessity use at least one loop of information flow providing feedback." (Alan Scrivener, "A Curriculum for Cybernetics and Systems Theory", 2012)

Systems Engineering: Chaos Theory (Definitions)

"A scientific approach – research effort which is based on examining behaviors of nonlinear dynamical systems, which are highly sensitive to their initial conditions." (Utku Köse & Ahmet Arslan, "Chaotic Systems and Their Recent Implementations on Improving Intelligent Systems", 2014)

"Study of deterministic behaviours that depend on initial conditions in physical, natural and social sciences." (Ayşe G Gözüm, "Evaluating HRM Functions within the Context of Chaos and Complexity Theory", 2016)

"The mathematical framework for understanding irregular and erratic fluctuations in economic cycles, financial markets, weather, other complex phenomenon, or non-linear systems with many variables." (Kijpokin Kasemsap, "Utilizing Complexity Theory and Complex Adaptive Systems in Global Business", 2016)

"The study of the behavior of dynamical systems that are highly sensitive to initial conditions." (Rohnn B Sanderson, "Understanding Chaos as an Indicator of Economic Stability", 2016)

"The theory that emerged from mathematics and used widely by other disciplines which concentrates on the dynamical systems." (Çağlar Doğru, "Leader-Member Exchange and Transformational Leadership in Chaos and Complexity", 2016)

"A field of study that explains nonlinear or dynamical systems." (Sharon E Norris, "Examining the Strategic Leadership of Organizations Using Metaphor: Brains and Flux-Interconnected and Interlocked", 2017)

"Chaos theory is the branch of mathematics deals with complicated linear dynamic systems." (Anandkumar R &  Kalpana R, "A Review on Chaos-Based Image Encryption Using Fractal Function", 2020)

"Suggests a randomness of understanding around complex patterns. These may be described as dynamic systems that reflect irregularities and is extremely sensitive to negligible fluctuations or moderations in situation." (Caroline M Crawford et al, "Social Learning Through a Participative Storytelling Framework: Rethinking the Essence of Course Engagement", 2021)

"Chaos theory is a branch of mathematics focusing on the study of chaos - dynamical systems whose random states of disorder and irregularities are governed by underlying patterns and deterministic laws that are highly sensitive to initial conditions." (Nima Norouzi, "Criminal Policy, Security, and Justice in the Time of COVID-19", 2022)