Toward a practice of autonomous systems : proceedings of the first European Conference on Artificial Life
著者
書誌事項
Toward a practice of autonomous systems : proceedings of the first European Conference on Artificial Life
（Complex adaptive systems）
MIT Press, c1992
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注記
Selected papers from the first European Conference on Artificial Life, held in Paris, France in December 1991
Includes bibliographical references and index
内容説明・目次
内容説明
Artificial life embodies a recent and important conceptual step in modem science: asserting that the core of intelligence and cognitive abilities is the same as the capacity for living. The recent surge of interest in artificial life has pushed a whole range of engineering traditions, such as control theory and robotics, beyond classical notions of goal and planning into biologically inspired notions of viability and adaptation, situatedness and operational closure. These proceedings serve two important functions: they address bottom-up theories of artificial intelligence and explore what can be learned from simple models such as insects about the cognitive processes and characteristic autonomy of living organisms, while also engaging researchers and philosophers in an exciting examination of the epistemological basis of this new trend.
Topics
Artificial Animals * Genetic Algorithms * Autonomous Systems * Emergent Behaviors * Artificial Ecologies * Immunologic Algorithms * Self-Adapting Systems * Emergent Structures * Emotion And Motivation * Neural Networks * Coevolution * Fitness Landscapes
Contributors
H. Bersini, Domenico Parisi, Rodney A. Brooks, Christopher G. Langton, S. Kauffman, J.-L. Denenbourg, Pattie Maes, John Holland, T. Smithersm H. Swefel, H. Muhlenbein
目次
- Part 1 Autonomous robots: artificial life and real robots, Rodney A. Brooks
- concept formation as emergent phenomena, Mukesh J. Patel and Uwe Schnepf
- distributed adaptive control - a paradigm for designing autonomous agents, Rolf Pfeifer and Paul Verschure
- taking eliminative materialism seriously - a methodology for autonomous systems research, Tim Smithers
- an adaptable mobile robot, Leslie Pack Kaelbling
- learning behaviour networks from experience, Pattie Maes
- characterizing adaptation by constraint, Ian Horswill
- on the self-organizing properties of topological maps, Didier Keymeulen and Jo Decuyper
- massively parallel evolution of recurrent networks - an approach to temporal processing, Piet Spiessens and Jan Torreele
- neural networks for visual tracking in an artificial fly, Dave Cliff
- an approach to sensorimotor relevance, Eric Dedieu and Emmanuel Mazer
- using motor actions for location recognition, Ulrich Nehmzow and Tim Smithers
- the application of temporal difference learning to the neural control of quadruped locomotion, Martin Snaith and Owen Holland
- evolution of subsumption using genetic programming, John R. Koza. Part 2 Swarm intelligence: warm-made architectures, Jean-Louis Deneubourg, et al
- distributed optimization by ant colonies, Alberto Colorni, et al
- emergent colonization in an artificial ecology, Andrew M. Assad and Norman H. Packard
- the maximum entropy principle and sensing in swarm intelligence, Gerardo Beni and Susan Hackwood
- a behavioural simulation model for the study of emergent social structures, Alexis Drogoul, et al
- interactive evolution of dynamical systems, Karl Sims
- simulating co-evolution with mimetism, Nicolas Meuleau
- dynamics of artificial markets - speculative markets and emerging "Common Sense" knowledge, Christian Nottola, et al
- harvesting by a group of robots, S. Goss and J.L. Deneubourg. Part 3 Learning and evolution: learning, behaviour and evolution, Domenico Parisi, et al
- immune network and adaptive control, Hugues Bersini
- genetic self-learning, Frank Hoffmeister and Thomas Back
- Darwin's continent cycle theory and its simulation by the prisoner's dilemma, Heinz Muhlenbein
- the royal road for genetic algorithms - fitness landscapes and GA performance, Melanie Mitchell, et al
- using marker-based genetic encoding of neural networks to evolve finite-state behaviour, Brad Fullmer and Risto Miikkulainen
- self-adaptation in genetic algorithms, Thomas Back
- steerable GenNets - the genetic programming of steerable behaviours in GenNets, Hugo de Garis
- an action based neural network for adaptive control - the tank case study, Antonio Rizzo and Neil Burgess
- a model of formal neural network for non-supervised learning and recognition of temporal sequences, Bruno Gas. (Part contents)
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