|
From Animals to Animats 2: SAB'92 |
||||||||||||
|
From Animals to Animats 2
Proceedings of the Second International Conference on Simulation of Adaptive Behavioredited by Jean-Arcady Meyer, Herbert L. Roitblat, and Stewart W. WilsonMore than sixty contributions in From Animals to Animats 2 by researchers in ethology, ecology, cybernetics, artificial intelligence, robotics, and related fields investigate behaviors and the underlying mechanisms that allow animals and, potentially, robots to adapt and survive in uncertain environments. Topics covered: The Animat Approach to Adaptive Behavior. Perception and Motor Control. Action Selection and Behavioral Sequences. Cognitive Maps and Internal World Models. Learning. Evolution. Collective Behavior.
CONTENTS
Preface x
THE ANIMAT APPROACH TO ADAPTIVE BEHAVIOR
Behavior-Based Artificial Intelligence 2 Pattie Maes
Environment Structure and Adaptive Behavior From the Ground Up 11 Peter M. Todd and Stewart W. Wilson
Evolutionary Wanderlust: Sexual Selection with Directional Mate Preferences 21 Geoffrey F. Miller and Peter M. Todd
Designing Efficiently Navigating Non-Goal-Directed Robots 31 Rolf Pfeifer and Paul F. M. J. Verschure
PERCEPTION AND MOTOR CONTROL
Anuran Visuomotor Coordination for Detour Behavior: From Retina to Motor Schemas 42 Michael A. Arbib and Hyun Bong Lee
Artificial Neural Nets for Controlling a 6-Legged Walking System 52 Holk Cruse, Uwe Müller-Wilm, and Jeffrey Dean
A Neural Network Based Behavior Hierarchy for Locomotion Control 61 Sunil Cherian and Wade 0. Troxell
A Qualitative Dynamical Analysis of Evolved Locomotion Controllers 71 John C. Gallagher and Randall D. Beer
Neuronal Parameter Maps and Signal Processing 81 Richard A. Altes
Representation and Processing of Acoustic Information in a Biomimetic Neural Network 90 Herbert L. Roitblat, Patrick W. B. Moore, David A. Helweg, and Paul E. Nachtigall
An Integrated Computational Model of a Perceptual-Motor System 100 William R. Uttal, Thomas Shepherd, Sriram Dayanand, and Robb Lovell
Reactive Behaviors of Fast Mobile Robots in Unstructured Environments: Sensor-Based Control and Neural Networks 108 R. Zapata, P. Lepinay, C. Novales, and P. Deplanques
The Adaptive Nature of 3D Perception 116 Allen Brookes
Propulsion and Guidance in a Simulation of the Worm C. Elegans 122 Ralph Hartley
A Simple, Cheap, and Robust Visual Navigation System 129 Ian Horswill
ACTION SELECTION AND BEHAVIORAL SEQUENCES
The Use of Hierarchies for Action Selection 138 Toby Tyrrell
Two Methods for Hierarchy Learning in Reinforcement Environments 148 Mark Ring
Should I Stay or Should I Go: Coordinating Biological Needs with Continuously-updated Assessments of the Environment 156 Liane M. Gabora
Extensions of the Associative Control Process (ACP) Network: Hierarchies and Provable Optimality 163 Leemon C. Baird In and A. Harry Klopf
Behavior Networks and Force Fields for Simulating Spinal Reflex Behaviors of the Frog 172 Simon Giszter
The Ariadne's Clew Algorithm 182 Emmanuel Mazer, Juan Manuel Ahuactzin, El- Ghazali Talbi, and Pierre Bessiere
Dynamic Selection of Action Sequences 189 Feliz Ribeiro, Jean-Paul Barthes, and Eugenio Oliveira
Planning Simple Trajectories Using Neural Subgoal Generators 196 Jurgen Schmidhuber and Reiner Wahnsiedler
A Note on Rate-Sensitive Habituation 203 J. E. R. Staddon
COGNITIVE MAPS AND INTERNAL WORLD MODELS
Categorization, Representations, and The Dynamics of System-Environment Interaction: A Case Study in Autonomous Systems 210 Paul F. M. J. Verschure and Rolf Pfeifer
A Directional Spreading Activation Network for Mobile Robot Navigation 218 David Kortenkamp and Eric Chown
Memorizing and Representing Route Scenes 225 Saburo Tsuff and Shigang Li
Building Long-Range Cognitive Maps Using Local Landmarks 233 Tony J. Prescott and John E. W. Mayhew
Dynamics of Spatial Navigation: An Adaptive Neural Network 243 Nestor A. Schmajuk and H. T. Blair
LEARNING
Modeling Nervous System Function with a Hierarchical Network of Control Systems That Learn 254 A. Harry Klopf, James S. Morgan, and Scott E. Weaver
An Optimization-Based Categorization of Reinforcement Learning Environments 262 Michael L. Littman
Reinforcement Learning with Hidden States 271 Long-Ji Lin and Tom M. Mitchell
Efficient Learning and Planning within the Dyna Framework 281 Jing Peng and Ronald J. Williams
Increasing Behavioural Repertoire in a Mobile Robot 291 Ulrich Nehmzow, Tim Smithers, and Brendan McGonigle
Learning Biped Robot Obstacle Crossing 298 Thomas Ulrich Vogel
Learning to Control an Autonomous Robot by Distributed Genetic Algorithms 305 Marco Colombetti and Marco Dorigo
Temporary Memory for Examples Can Speed Learning in a Simple Adaptive System 313 Lawrence Davis, Stewart Wilson, and David Orvosh
Implementing Inner Drive Through Competence Reflection 321 Alexander Linden and Frank Weber
Dynamic Flight Control with Adaptive Coarse Coding 327 Bruce E. Rosen and James M. Goodwin
Learning via Task Decomposition 337 Josh Tenenberg, Jonas Karlsson, and Steven Whitehead
EVOLUTION
Neural Networks with Motivational Units 346 Federico Cecconi and Domenico Parisi
Evolutionary Learning of Predatory Behaviors Based on Structured Classifiers 356 Hitoshi Iba, Hugo de Garis, and Tetsuya Higuchi
Issues in Evolutionary Robotics 364 Inman Harvey, Philip Husbands, and Dave Cliff
Evolving Visually Guided Robots 374 Dave Cliff, Philip Husbands, and Inman Harvey
An Evolved, Vision-Based Behavioral Model of Coordinated Group Motion 384 Craig W. Reynolds
Evolution of Herding Behavior in Artificial Animals 393 Gregory M. Werner and Michael G. Dyer
An Evolutionary Approach to Cognition 400 Dwight Deugo and Franz Oppacher
Emergence of Nest-Based Foraging Strategies in Ecosystems of Neural Networks 410 Dario Floreano
Evolving Hardware with Genetic Learning: A Filst Step Towards Building a Darwin Machine 417 Tetsuya Higuchi, Tatsuya Niwa, Toshio Tanaka, Hitoshi Iba, Hugo de Garis, and Tatsumi Furuya
Evolving Artificial Insect Brains for Artificial Compound Eye Robotics 425 Luis R. Lopez and Robert E. Smith
COLLECTIVE BEHAVIOR
Designing Emergent Behaviors: From Local Interactions to Collective Intelligence 432 Maja J. Mataric
Adaptive Action Selection for Cooperative Agent Teams 442 Lynne E. Parker
From Tom Thumb to the Dockers: Some Experiments with Foraging Robots 451 Alexis Drogoul and Jacgues Ferber
Collective Robotic Intelligence 460 C. Ronald Kube and Hong Zhang
Collective Choice of Strategic Type 469 Chisato Numaoka and Akikazu Takeuchi
An Adaptive Communication Protocol for Cooperating Mobile Robots 478 Holly Yanco and Lynn Andrea Stein
Dimensions of Communication and Social Organization in Multi-Agent Robotic Systems 486 Ronald C. Arkin and J. David Hobbs
Evolution of Trading Strategies Among Heterogeneous Artificial Economic Agents 494 Andrea Beltratti and Sergio Margarita
Action Selection and Learning in Multi-Agent Environments 502 Gerhard Weiss
ONE-PAGE SUMMARIES
Structure from Associative Learning 512 John H. Andreae, Shaun W. Ryan, and Mark L. Tomlinson
The Roots of Motivation 513 Christian Balkenius
Learning Continuous-Space Navigation Heuristics in Real Time 514 Gregory D. Benson and Armand Prieditis
The Adaptive Power of Affect: Learning in the SESAME Architecture 515 Eric Chown Model of a Behaviour Based Control Architecture 516 Luis Correia and A. Steiger-Garçao
Comparing Robot and Animal Behavior 517 Bridget Hallam and Gillian Hayes
An Embodied Neurally-Based Algorithm for Optimal Action Selection 518 Owen Holland and Martin Snaith
Why Should We Build Artificial Worms and How? 519 Oded Maler Creative Perception 520 M. A. Rodrigues and M. H. Lee
Collective Behavior of Silicon Microrobots 521 Isao Shimoyama, Toshio Watanabe, Yoshihiko Kuwana, and Hirofumi Miura
An Analog VLSI Model of Central Pattern Generation in the Medicinal Leech 522 Micah S. Siegel
Author Index 523
|
||||||||||||
|
|
|||||||||||||
18:18 GMT; 22/03/08 |
Comments or Questions? Contact Us.. Copyright © 2008, ISAB. All rights reserved. |
||||||||||||