From Animals to Animats 3

Proceedings of the Third International Conference on Simulation of Adpative Behavior
Overview

August 8-12, 1994, Brighton, England

From Animals to Animats 3 brings together research intended to advance the fron tier of an exciting new approach to understanding intelligence. The contributors represent a broad range of interests from artificial intelligence and robotics to ethology and the neurosciences. Unifying these approaches is the notion of "animat"—an artificial animal, either simulated by a computer or embodied in a robot, which must survive and adapt in progressively more challenging environments. The 58 contributions focus particularly on well-defined models, computer simulations, and built robots in order to help characterize and compare various principles and architectures capable of inducing adaptive behavior in real or artificial animals.

Topics include:
- Individual and collective behavior.
- Neural correlates of behavior.
- Perception and motor control.
- Motivation and emotion.
- Action selection and behavioral sequences.
- Ontogeny, learning, and evolution.
- Internal world models and cognitive processes.
- Applied adaptive behavior.
- Autonomous robots.
- Heirarchical and parallel organizations.
- Emergent structures and behaviors.
- Problem solving and planning.
- Goal-directed behavior.
- Neural networks and evolutionary computation.
- Characterization of environments.

A Bradford Book

Table of Contents

  1. Preface
  2. 1. From SAB90 to SAB94: Four Years of Animat Research

    Jean-Arcady Meyer and Agnès Guillot

  3. 2. Mechanism and Process in Animal Behavior: Models of Animals, Animals as Models

    Herbert L. Roitblat

  4. 3. Coherent Behavior from Many Adaptive Processes

    Rodney A. Brooks

  5. 4. Stability in Adaptation and Learning

    Jean-Jacques E. Slotine

  6. 5. Modeling the Role of Cerebellum in Prism Adaptation

    Michael A. Arbib, Nicolas Schweighofer and W. T. Thach

  7. 6. Robotic Experiments in Cricket Phonotaxis

    Barbara Webb

  8. 7. How to Watch Your Step: Biological Evidence and an Initial Model

    Patrick R. Green

  9. 8. On Why Better Robots Make it Harder

    Tim Smithers

  10. 9. Insect Vision and Olfaction: Different Neural Architectures for Different Kinds of Sensory Signal?

    d. Osorio, Wayne M. Getz and Jürgen Rybak

  11. 10. The Interval Reduction Strategy for Monitoring Cupcake Problems

    Paul R. Cohen, Marc S. Atkin and Eric A. Hansen

  12. 11. Visual Control of Altitude and Speed in a Flying Agent

    Fabrizio Mura and Nicolas Franceschini

  13. 12. What Is Cognitive and What Is Cognitive?

    Frederick Toates

  14. 13. Action-Selection in Hamsterdam: Lessons from Ethology

    Bruce Blumberg

  15. 14. Behavioral Dynamics of Escape and Avoidance: A Neural Network Approach

    Nestor A. Schmajuk

  16. 15. Organizing an Animat's Behavioural Repertoires Using Kohonen Feature Maps

    Nigel Ball

  17. 16. Action Selection for Robots in Dynamic Environments through Inter-behaviour Bidding

    Michael K. Sahota

  18. 17. An Hierarchical Classifier System Implementing a Motivationally Autonomous Animat

    Jean-Yves Donnart and Jean-Arcady Meyer

  19. 18. Using Second Order Neural Connections for Motivation of Behavioral Choices

    Gregory M. Werner

  20. 19. Spatial Learning and Representation in Animats

    Tony J. Prescott

  21. 20. Location Recognition in Rats and Robots

    William D. Smart and John Hallam

  22. 21. Emergent Functionality in Human Infants

    Julie C. Rutkowska

  23. 22. Connectionist Environment Modelling in a Real Robot

    William Chesters and Gillian Hayes

  24. 23. A Hybrid Architecture for Learning Continuous Environmental Models in Maze Problems

    A. G. Pipe, T. C. Fogarty and A. Winfield

  25. 24. A Place Navigation Algorithm Based on Elementary Computing Procedures and Associative Memories

    Simon Benhamou, Pierre Bovet and Bruno Poucet

  26. 25. Self-Organizing Topographic Maps and Motor Planning

    Pietro Morasso and Vittorio Sanguineti

  27. 26. The Effect of Memory Length on the Foraging Behavior of a Lizard

    Sharoni Shafir and Jonathan Roughgarden

  28. 27. The Blind Breeding the Blind: Adaptive Behavior without Looking

    Peter M. Todd, Stewart W. Wilson, Anil B. Somayaji and Holly A. Yanco

  29. 28. Memoryless Policies: Theoretical Limitations and Practical Results

    Michael L. Littman

  30. 29. A Comparison of Q-Learning and Classifier Systems

    Marco Dorigo and Hugues Bersini

  31. 30. Paying Attention to What's Important: Using Focus of Attention to Improve Unsupervised Learning

    Leonard N. Foner and Pattie Maes

  32. 31. Learning Efficient Reactive Behavioral Sequences from Basic Reflexes in a Goal-Directed Autonomous Robot

    José del R. Millá

  33. 32. The Importance of Leaky Levels for Behavior-Based AI

    Gregory M. Saunders, John F. Kolen and Jordan B. Pollack

  34. 33. A Topological Neural Map for On-line Learning: Emergence of Obstacle Avoidance in a Mobile Robot

    Philippe Gaussier and Stephane Zrehen

  35. 34. Reinforcement Tuning of Action Synthesis and Selection in a 'Virtual Frog'

    Simon Giszter

  36. 35. Achieving Rapid Adaptations in Robots by Means of External Tuition

    Ulrich Nehmzow and Brendan McGonigle

  37. 36. Two-Link-Robot Brachiation with Connectionist Q-Learning

    Fuminori Saito and Toshio Fukuda

  38. 37. An Architecture for Learning to Behave

    Ahsley M. Aitken

  39. 38. Reinforcement Learning for Homeostatic Endogenous Variables

    Hugues Bersini

  40. 39. An Architecture for Representing and Learning Behaviors by Trial and Error

    Pascal Blanchet

  41. 40. A Distributed Adaptive Control System for a Quadruped Mobile Robot

    Bruce L. Digney and M. M. Gupta

  42. 41. Reinforcement Learning with Dynamic Covering of State-Action Space: Partitioning Q-Learning

    Rémi Munos and Jocelyn Patinel

  43. 42. The Five Neuron Trick: Using Classical Conditioning to Learn How to Seek Light

    Tom Scutt

  44. 43. Adaptation in Dynamic Environments through a Minimal Probability of Exploration

    Gilles Venturini

  45. 44. Integrating Reactive, Sequential, and Learning Behavior Using Dynamical Neural Networks

    Brian Yamauchi and Randall Beer

  46. 45. Seeing The Light: Artificial Evolution, Real Vision

    Inman Harvey, Phil Husbands and Dave Cliff

  47. 46. Evolution of Corridor Following Behavior in a Noisy World

    Craig W. Reynolds

  48. 47. Protean Behavior in Dynamic Games: Arguments for the Co-Evolution of Pursuit-Evasion Tactics

    Geoffrey F. Miller and Dave Cliff

  49. 48. Automatic Creation of an Autonomous Agent: Genetic Evolution of a Neural-Network Driven Robot

    Dario Floreano and Francesco Mondada

  50. 49. The Effect of Parasitism on the Evolution of a Communication Protocol in an Artificial Life Simulation

    Phil Robbins

  51. 50. Towards Robot Cooperation

    David McFarland

  52. 51. A Case Study in the Behavior-Oriented Design of Autonomous Agents

    Luc Steels

  53. 52. Learning to Behave Socially

    Maja J. Mataric

  54. 53. Signalling and Territorial Aggression: An Investigation by Means of Synthetic Behavioural Ecology

    Peter de Bourcier and Michael Wheeler

  55. 54. Integration of Reactive and Telerobotic Control in Multi-agent Robotic Systems

    Ronald C. Arkin and Khaled S. Ali

  56. 55. MINIMEME: Of Life and Death in the Noosphere

    Stéphane Bura

  57. 56. Learning Coordinated Motions in a Competition for Food between Ant Colonies

    Masao Kubo and Yukinori Kakazu

  58. 57. Emergent Colonization and Graph Partitioning

    Pascale Kuntz and Dominique Snyers

  59. 58. Diversity and Adaptation in Populations of Clustering Ants

    Erik D. Lumer and Baldo Faieta

  60. Author Index