From Animals to Animats 2

Proceedings of the Second International Conference on Simulation of Adaptive Behavior
Overview

More 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.

Table of Contents

  1. Preface
  2. I. THE ANIMAT APPROACH TO ADAPTIVE BEHAVIOR
  3. 1. Behavior-Based Artificial Intelligence

    Pattie Maes

  4. 2. Environment Structure and Adaptive Behavior from the Ground Up

    Peter M. Todd and Stewart W. Wilson

  5. 3. Evolutionary Wanderlust: Sexual Selection with Directional Mate Preferences

    Geoffrey F. Miller and Peter M. Todd

  6. 4. Designing Efficiently Navigating Non-Goal-Directed Robots

    Rolf Pfeifer and Paul F. M. J. Verschure

  7. II. PERCEPTION AND MOTOR CONTROL
  8. 5. Anuran Visuomotor Coordination for Detour Behavior: From Retina to Motor Schemas

    Michael A. Arbib and Hyun Bang Lee

  9. 6. Artificial Neural Nets for Controlling a 6-Legged Walking System

    Holk Cruise, Uwe Müller-Wilm and Jeffrey Dean

  10. 7. A Neural Network Based Behavior Hierarchy for Locomotion Control

    Sunil Cherian and Wade O. Troxell

  11. 8. A Qualitative Dynamical Analysis of Evolved Locomotion Controllers

    John C. Gallagher and Randall D. Beer

  12. 9. Neuronal Parameter Maps and Signal Processing

    Richard A. Altes

  13. 10. Representation and Processing of Acoustic Information in a Biomimetic Neural Network

    Herbert L. Roitblat, Patrick W. B. Moore, David A. Helweg and Paul E. Nachtigall

  14. 11. An Integrated Computational Model of a Perceptual-Motor System

    William R. Uttal, Thomas Shepherd, Sriram Dayanand and Robb Lovell

  15. 12. Reactive Behaviors of Fast Mobile Robots in Unstructured Environments: Sensor-based Control and Neural Networks

    R. Zapata, P. Lépinay, C. Novales and P. Deplanques

  16. 13. The Adaptive Nature of 3D Perception

    Allen Brookes

  17. 14. Propulsion and Guidance in a Simulation of the Worm

    Ralph Hartley

  18. 15. A Simple, Cheap, and Robust Visual Navigation System

    Ian Horswill

  19. III. ACTION SELECTION AND BEHAVIORAL SEQUENCES
  20. 16. The Use of Hierarchies for Action Selection

    Toby Tyrrell

  21. 17. Two Methods for Hierarchy Learning in Reinforcement Environments

    Mark Ring

  22. 18. Should I Stay or Should I Go: Coordinating Biological Needs with Continuously-updated Assessments of the Environment

    Liane M. Gabora

  23. 19. Extensions of the Associative Control Process (ACP) Network: Hierarchies and Provable Optimality

    Leemon C. Baird III and A. Harry Klopf

  24. 20. Behavior Networks and Force Fields for Simulating Spinal Reflex Behaviors of the Frog

    Simon Giszter

  25. 21. The Ariadne's Clew Algorithm

    Emmanuel Mazer, Juan Maneul Ahuactzin, El-Ghazali Talbi and Pierre Bessiere

  26. 22. Dynamic Selection of Action Sequences

    Feliz Ribeiro, Jean-Paul Barthès and Eugéenio Oliveira

  27. 23. Planning Simple Trajectories Using Neural Subgoal Generators

    Jürgen Schmidhuber and Reiner Wahnsiedler

  28. 24. A Note on Rate-Sensitive Habituation

    J. E. R. Staddon

  29. IV. COGNITIVE MAPS AND INTERNAL WORLD MODELS
  30. 25. Categorization, Representations, and the Dynamics of System-Environment Interaction: A Case Study in Autonomous Systems

    Paul F. M. J. Verschure and Rolf Pfeifer

  31. 26. A Directional Spreading Activation Network for Mobile Robot Navigation

    David Kortenkamp and Eric Chown

  32. 27. Memorizing and Representing Route Scenes

    Saburo Tsuji and Shigang Li

  33. 28. Building Long-range Cognitive Maps using Local Landmarks

    Tony J. Prescott and John E. W. Mayhew

  34. 29. Dynamics of Spatial Navigation: An Adaptive Neural Network

    Nestor A. Schmajuk and H. T. Blair

  35. V. LEARNING
  36. 30. Modeling Nervous System Function with a Hierarchical Network of Control Systems that Learn

    A. Harry Klopf, James S. Morgan and Scott E. Weaver

  37. 31. An Optimization-based Categorization of Reinforcement Learning Environments

    Michael L. Littman

  38. 32. Reinforcement Learning with Hidden States

    Long-Ji Lin and Tom M. Mitchell

  39. 33. Efficient Learning and Planning within the Dyna Framework

    Jing Peng and Ronald J. Williams

  40. 34. Increasing Behavioural Repertoire in a Mobile Robot

    Ulrich Nehmzow, Tim Smithers and Brendand McGonigle

  41. 35. Learning Biped Robot Obstacle Crossing

    Thomas Ulrich Vogel

  42. 36. Learning to Control an Autonomous Robot by Distributed Genetic Algorithms

    Marco Colombetti and Marco Dorigo

  43. 37. Temporary Memory for Examples Can Speed Learning in a Simple Adaptive System

    Lawrence Davis, Stewart Wilson and David Orvosh

  44. 38. Implementing Inner Drive through Competence Reflection

    Alexander Linden and Frank Weber

  45. 39. Dynamic Flight Control with Adaptive Coarse Coding

    Bruce E. Rosen and James M. Goodwin

  46. 40. Learning via Task Decomposition

    Josh Tenenberg, Jonas Karlsson and Steven Whitehead

  47. VI. EVOLUTION
  48. 41. Neural Networks with Motivational Units

    Federico Cecconi and Domenico Parisi

  49. 42. Evolutionary Learning of Predatory Behaviors Based on Structured Classifiers

    Hitoshi Iba, Hugo de Garis and Tetsuya Higuchi

  50. 43. Issues in Evolutionary Robotics

    Inman Harvey, Philip Husbands and Dave Cliff

  51. 44. Evolving Visually Guided Robots

    Dave Cliff, Philip Husbands and Inman Harvey

  52. 45. An Evolved, Vision-Based Behavioral Model of Coordinated Group Motion

    Craig W. Reynolds

  53. 46. Evolution of Herding Behavior in Artificial Animals

    Gregory M. Werner and Michael G. Dyer

  54. 47. An Evolutionary Approach to Cognition

    Dwight Deugo and Franz Oppacher

  55. 48. Emergence of Nest-Based Foraging Strategies in Ecosystems of Neural Networks

    Dario Floreano

  56. 49. Evolving Hardware with Genetic Learning: A First Step Towards Building a Darwin Machine

    Tetsuya Higuchi, Tatsuya Niwa, Tosho Tanaka, Hitoshi Iba, Hugo de Garis and Tatsumi Furuya

  57. 50. Evolving Artificial Insect Brains for Artificial Compound Eye Robotics

    Luis R. Lopez and Robert E. Smith

  58. VII. COLLECTIVE BEHAVIOR
  59. 51. Designing Emergent Behaviors: From Local Interactions to Collective Intelligence

    Maja J. Mataric

  60. 52. Adaptive Action Selection for Cooperative Agent Teams

    Lynne E. Parker

  61. 53. From Tom Thumb to the Dockers: Some Experiments with Foraging Robots

    Alexis Drogoul and Jacques Ferber

  62. 54. Collective Robotic Intelligence

    C. Ronald Kube and Hong Zhang

  63. 55. Collective Choice of Strategic Type

    Chisato Numaoka and Akikazu Takeuchi

  64. 56. An Adaptive Communication Protocol for Cooperating Mobile Robots

    Holy Yanco and Lynn Andrea Stein

  65. 57. Dimensions of Communication and Social Organization in Multi-agent Robotic Systems

    Ronald C. Arkin and J. David Hobbs

  66. 58. Evolution of Trading Strategies Among Heterogeneous Artificial Economic Agents

    Andrea Beltratti and Sergio Margarita

  67. 59. Action Selection and Learning in Multi-Agent Environments

    Gerhard Weiss

  68. VIII. ONE-PAGE SUMMARIES
  69. 60. Structure from Associative Learning

    John H. Andreae, Shuan W. Ryan and Mark L. Tomlinson

  70. 61. The Roots of Motivation

    Christian Balkenius

  71. 62. Learning Continuous-Space Navigation Heuristics in Real Time

    Gregory D. Benson and Armand Prieditis

  72. 63. The Adaptive Power of Affect: Learning in the SESAME Architecture

    Eric Chown

  73. 64. Model of a Behaviour Based Control Architecture

    Luís Correia and A. Steiger-Garção

  74. 65. Comparing Robot and Animal Behavior

    Bridget Hallam and Gillian Hayes

  75. 66. An Embodied Neurally-based Algorithm for Optimal Action Selection

    Owen Holland and Martin Smith

  76. 67. Why Should We Build Artificial Worms and How?

    Oded Maler

  77. 68. Creative Perception

    M. A. Rodrigues and M. H. Lee

  78. 69. Collective Behavior of Silicon Microrobots

    Isao Shimoyama, Toshio Watanabe, Yoshihiko Kuwana and Hirofumi Miura

  79. 70. An Analog VLSI Model of Central Pattern Generation in the Medicinal Leech

    Micah S. Siegel

  80. Author Index