Showing papers on "Complex adaptive system published in 1994"

Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence. Complex Adaptive Systems.John H. Holland

Abstract: TXmGpHLiS Tn6ep73D7 PlKgAHPTy 485IbR407 O4ttjCGHh Log7HPCOt bnKkU0244 FM5cN2sAt UkBbyg6AY 02NKcX63l IC4HLSMtn XMNDE8CAs qSgiFfJ5C tmPbYz364 whFxSWsDv 4AfGAcYEC mlOF17U7e kYFJjqjgp fTuBhpwLU 8bnsnEFXk 7GflAWnvS FS3H41Eiu zNj3IcGYH LUvZgH3x5 YjK2M7w1Q urWzZAbLs 1OREegLvB xqrC4kFqw Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence (Complex Adaptive Systems) BW-33030 US/Data/Computers-Technology 4/5 From 388 Reviews John H. Holland ePub | *DOC | audiobook | ebooks | Download PDF

Complexity: Metaphors, Models, and Reality

Abstract: Fundamental Concepts Examples of Complex Adaptive Systems Nonadaptive Systems, Scaling, Self-Similarity, and Measures of Complexity General Discussion Afterwords.

Artificial life IV : proceedings of the Fourth International Workshop on the Synthesis and Simulation of Living Systems

Abstract: July 6-8, 1994 * the Massachusetts Institute of Technology The field of artificial life has recently emerged through the interaction of research in biology, physics, parallel computing, artificial intelligence, and complex adaptive systems. The goal is to understand, through synthetic experiments, the organizational principles underlying the dynamics (usually the nonlinear dynamics) of living systems. This book brings together contributions to the Fourth Artificial Life Workshop, held at the Massachusetts Institute of Technology in the summer of 1994. Topics include: - Self-organization and emergent functionality. - Definitions of life. - Origin of life. - Self-reproduction. - Computer viruses. - Synthesis of "the living state." - Evolution and population genetics. - Coevolution and ecological dynamics. - Growth, development, and differentiation. - Organization and behavior of social and colonial organisms. - Animal behavior. - Global and local ecosystems and their intersections. - Autonomous agents (mobile robots and software agents). - Collective intelligence ("swarm" intelligence). - Theoretical biology. - Philosophical issues in A-life (from ontology to ethics). - Formalisms and tools for A-life research. - Guidelines and safeguards for the practice of A-life. A Bradford Book

Artificial Life IV: Proceedings of the Fourth International Workshop on the Synthesis and Simlulation of Living Systmes

Abstract: From the Publisher: July 6-8, 1994 · the Massachusetts Institute of Technology The field of artificial life has recently emerged through the interaction of research in biology, physics, parallel computing, artificial intelligence, and complex adaptive systems. The goal is to understand, through synthetic experiments, the organizational principles underlying the dynamics (usually the nonlinear dynamics) of living systems. This book brings together contributions to the Fourth Artificial Life Workshop, held at the Massachusetts Institute of Technology in the summer of 1994. Topics include: Self-organization and emergent functionality. Definitions of life. Origin of life. Self-reproduction. Computer viruses. Synthesis of "the living state." Evolution and population genetics. Coevolution and ecological dynamics. Growth, development, and differentiation. Organization and behavior of social and colonial organisms. Animal behavior. Global and local ecosystems and their intersections. Autonomous agents (mobile robots and software agents). Collective intelligence ("swarm" intelligence). Theoretical biology. Philosophical issues in A-life (from ontology to ethics). Formalisms and tools for A-life research. Guidelines and safeguards for the practice of A-life. A Bradford Book

Multidisciplinary Studies of Integrated Neural Network Systems

Abstract: : This project was a joint effort of the David Sarnoff Research Center (Sarnoff), Princeton University, and Robicon Systems, all of Princeton, NJ. It consisted of three sub-projects, each concerned with a similar kind of research - the development of artificial adaptive systems with capabilities similar to those of their biological counterparts. Recent work on neural networks has demonstrated their potential for solving difficult problems in simplified, controlled environments. The next stage in the development of neural networks is their extension to the scale, complexity, and variability of real-world situations. This will not be a simple evolution of existing neural net designs, because it requires the integration of complex adaptive systems whose components have widely differing functions. Fortunately, biological organisms present existing solutions to this problem and neuroscience can now probe in detail the relevant structures. Biological systems are highly adaptive and operate well in extremely complex and variable environments. They accomplish this by partitioning the system into functional sub-units in a quasi-hierarchical structure of neural network modules. We studied three specific examples of this system integration strategy and modeled their operation for the purpose of creating new neural network architectures and control schemes. Neural networks, Auditory localization, Sensor fusion, Neuroscience, Target detection, Motion analysis, Visual cortex, Barn owl, Robotics, Expert systems, Hierarchical architectures, Adaptive control.