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Andrzej Nowak (born June 12, 1953, in Warsaw) is a Polish psychologist, one of the founders of dynamical social psychology. He is a pioneer in applying computer simulations in social sciences.
Nowak received his M.A. (1978) and his Ph.D. (1987) from the University of Warsaw. His scientific interests include complex systems in psychology and social sciences.
Andrzej Nowak is currently a professor at the University of Warsaw, at the SWPS University of Social Sciences and Humanities, and at Florida Atlantic University. He is the director and founder of the Institute of Social Psychology of Internet and Communication at the Warsaw School of Social Sciences and Humanities. He is one of the founders of the Institut for Social Studies at the Warsaw University, where he is a director of the Center for Complex Systems Research.
Nowak is one of the world's leading experts on the modeling and computer simulation of social processes.[ citation needed ] Using cellular automata, he has modeled the emergence of public opinion in society and linear versus non-linear societal transitions.[ citation needed ] At FAU, he conducts both simulation and experimental research in the Dynamical Social Psychology Lab in collaboration with Robin Vallacher.[ citation needed ]
Current[ when? ] research projects include the use of cellular automata to simulate the emergence and maintenance of self-concept and linear and non-linear scenarios of societal change, the use of attractor neural networks to model interpersonal and group dynamics, and the use of coupled dynamical systems to simulate the emergence of personality through social coordination. Dr. Nowak is also developing software for identifying attractors (equilibrium states) in the temporal patterns of thought and emotion on the part of people diagnosed with various forms of mental illness.
.* Culicover, P. & Nowak, A. (2003). Dynamical Grammar: Minimalism, Acquisition, and Change (Foundations of Syntax). Oxford: Oxford University Press.
Systems theory is the transdisciplinary study of systems, i.e. cohesive groups of interrelated, interdependent components that can be natural or artificial. Every system has causal boundaries, is influenced by its context, defined by its structure, function and role, and expressed through its relations with other systems. A system is "more than the sum of its parts" by expressing synergy or emergent behavior.
The Game of Life, also known simply as Life, is a cellular automaton devised by the British mathematician John Horton Conway in 1970. It is a zero-player game, meaning that its evolution is determined by its initial state, requiring no further input. One interacts with the Game of Life by creating an initial configuration and observing how it evolves. It is Turing complete and can simulate a universal constructor or any other Turing machine.
Social simulation is a research field that applies computational methods to study issues in the social sciences. The issues explored include problems in computational law, psychology, organizational behavior, sociology, political science, economics, anthropology, geography, engineering, archaeology and linguistics.
Mathematical and theoretical biology, or biomathematics, is a branch of biology which employs theoretical analysis, mathematical models and abstractions of the living organisms to investigate the principles that govern the structure, development and behavior of the systems, as opposed to experimental biology which deals with the conduction of experiments to prove and validate the scientific theories. The field is sometimes called mathematical biology or biomathematics to stress the mathematical side, or theoretical biology to stress the biological side. Theoretical biology focuses more on the development of theoretical principles for biology while mathematical biology focuses on the use of mathematical tools to study biological systems, even though the two terms are sometimes interchanged.
Computational sociology is a branch of sociology that uses computationally intensive methods to analyze and model social phenomena. Using computer simulations, artificial intelligence, complex statistical methods, and analytic approaches like social network analysis, computational sociology develops and tests theories of complex social processes through bottom-up modeling of social interactions.
An agent-based model (ABM) is a computational model for simulating the actions and interactions of autonomous agents in order to understand the behavior of a system and what governs its outcomes. It combines elements of game theory, complex systems, emergence, computational sociology, multi-agent systems, and evolutionary programming. Monte Carlo methods are used to understand the stochasticity of these models. Particularly within ecology, ABMs are also called individual-based models (IBMs). A review of recent literature on individual-based models, agent-based models, and multiagent systems shows that ABMs are used in many scientific domains including biology, ecology and social science. Agent-based modeling is related to, but distinct from, the concept of multi-agent systems or multi-agent simulation in that the goal of ABM is to search for explanatory insight into the collective behavior of agents obeying simple rules, typically in natural systems, rather than in designing agents or solving specific practical or engineering problems.
An artificial society is an agent-based computational model for computer simulation in social analysis. It is mostly connected to the themes of complex systems, emergence, the Monte Carlo method, computational sociology, multi-agent systems, and evolutionary programming. While the concept was simple, actually realizing this conceptual point took a while. Complex mathematical models have been, and are, common; deceivingly simple models only have their roots in the late forties, and took the advent of the microcomputer to really get up to speed.
Generative science is an area of research that explores the natural world and its complex behaviours. It explores ways "to generate apparently unanticipated and infinite behaviour based on deterministic and finite rules and parameters reproducing or resembling the behavior of natural and social phenomena". By modelling such interactions, it can suggest that properties exist in the system that had not been noticed in the real world situation. An example field of study is how unintended consequences arise in social processes.
The Krasnow Institute for Advanced Study brings together researchers from many disciplines to study the phenomenon known as the mind. A unit of George Mason University, the Krasnow Institute also serves as a center for doctoral education in neuroscience. Research at the institute is funded by agencies such as the National Institutes of Health, the National Science Foundation and the Department of Defense.
In computer science and machine learning, cellular neural networks (CNN) or cellular nonlinear networks (CNN) are a parallel computing paradigm similar to neural networks, with the difference that communication is allowed between neighbouring units only. Typical applications include image processing, analyzing 3D surfaces, solving partial differential equations, reducing non-visual problems to geometric maps, modelling biological vision and other sensory-motor organs.
Computer simulation is a prominent method in organizational studies and strategic management. While there are many uses for computer simulation, most academics in the fields of strategic management and organizational studies have used computer simulation to understand how organizations or firms operate. More recently, however, researchers have also started to apply computer simulation to understand organizational behaviour at a more micro-level, focusing on individual and interpersonal cognition and behavior such as team working.
Humans have considered and tried to create non-biological life for at least 3000 years. As seen in tales ranging from Pygmalion to Frankenstein, humanity has long been intrigued by the concept of artificial life.
A quantum cellular automaton (QCA) is an abstract model of quantum computation, devised in analogy to conventional models of cellular automata introduced by John von Neumann. The same name may also refer to quantum dot cellular automata, which are a proposed physical implementation of "classical" cellular automata by exploiting quantum mechanical phenomena. QCA have attracted a lot of attention as a result of its extremely small feature size and its ultra-low power consumption, making it one candidate for replacing CMOS technology.
Norman H. Margolus is a Canadian-American physicist and computer scientist, known for his work on cellular automata and reversible computing. He is a research affiliate with the Computer Science and Artificial Intelligence Laboratory at the Massachusetts Institute of Technology.
A reversible cellular automaton is a cellular automaton in which every configuration has a unique predecessor. That is, it is a regular grid of cells, each containing a state drawn from a finite set of states, with a rule for updating all cells simultaneously based on the states of their neighbors, such that the previous state of any cell before an update can be determined uniquely from the updated states of all the cells. The time-reversed dynamics of a reversible cellular automaton can always be described by another cellular automaton rule, possibly on a much larger neighborhood.
SWPS University is a private non-profit university in Poland established in 1996 by three psychology professors, Andrzej Eliasz, Zbigniew Pietrasiński and Janusz Reykowski.
Artificial life is a field of study wherein researchers examine systems related to natural life, its processes, and its evolution, through the use of simulations with computer models, robotics, and biochemistry. The discipline was named by Christopher Langton, an American theoretical biologist, in 1986. In 1987 Langton organized the first conference on the field, in Los Alamos, New Mexico. There are three main kinds of alife, named for their approaches: soft, from software; hard, from hardware; and wet, from biochemistry. Artificial life researchers study traditional biology by trying to recreate aspects of biological phenomena.
Stochastic cellular automata or probabilistic cellular automata (PCA) or random cellular automata or locally interacting Markov chains are an important extension of cellular automaton. Cellular automata are a discrete-time dynamical system of interacting entities, whose state is discrete.
Muhammad Afzal Upal is a writer and a cognitive scientist with contributions to cognitive science of religion, machine learning for planning, and agent-based social simulation.
Crowd analysis is the practice of interpreting data on the natural movement of groups or objects. Masses of bodies, particularly humans, are the subjects of these crowd tracking analyses that include how a particular crowd moves and when a movement pattern changes. Researchers use the data to predict future crowd movement, crowd density, and plan responses to potential events such as those that require evacuation routes. Applications of crowd analysis can range from video game crowd simulation to security and surveillance.