Adaptive Behavior, 1 (2)

A topic of interdisciplinary research in neurobiology and neuroinformatics concerns visual pattern recognition by neuronal networks. Drawing on quantitative studies of visual releasers of prey catching in toads, it can be shown that moving objects are classified based on an evaluation of certain configurational features. The information regarding these features is provided in the manner of parallel distributed processing within a retino-pretectal-tectal interacting network. This processing structure is, to a considerable extent, modifiable and adaptive. Associative and nonassociative learning processes take advantage of loop operations involving various forebrain structures. An artificial neuronal net, applying some principles of the toad's visual system, is tested to promote the dialogue between neurobiology and engineering.

Key Words

visual pattern recognition; parallel distributed processing; implicit computation; sensorimotor codes; modulation; learning; gating; prey catching; toad

Pages 155-169

Kinematic Model of a Stick Insect as an Example of a Six- Legged Walking System

By Uwe Müller-Wilm, Holk Cruse, Jürgen Eltze, Jeffrey Dean, Hans-Jürgen Weidemann, Friederich Pfeiffer

Abstract The model proposed here describes the control of the leg movement of a six-legged walking system. It is based on biological data obtained from the stick insect. The model represents a combined treatment of realistic kinematics and of biologically motivated, adaptive gait generation. In contrast to previous biologically motivated models, it includes realistic legs with three joints and natural geometry and, with some simplifying assumptions, describes the movement of the joints and the tarsi. The results show that the information obtained from biological experiments can be incorporated into a model for a six-legged system that is able to walk at different speeds over irregular surfaces. The model shows a stable gait even when the movement of the legs is disturbed. The system can start walking beginning from arbitrary starting positions of the legs. Thus, the control system described here can be used to control a real walking machine.

Key Words

walking machine, leg coordination, motor control, stick insect

Pages 171-199

Evolution of Food-Foraging Strategies for the Caribbean Anolis Lizard Using Genetic Programming

By John R. Koza, Jonathan Roughgarden, and James P. Rice

Abstract: This article describes the recently developed genetic programming paradigm that genetically breeds a population of computer programs to solve problems. The article then demonstrates, step by step, how to apply genetic programming to a problem of behavioral ecology in biology--specifically, two versions of the problem of finding an optimal food- foraging strategy for the Caribbean Anolis lizard. A simulation of the adaptive behavior of the lizard is required to evaluate each possible adaptive control strategy considered for the lizard. The foraging strategy produced by genetic programming is close to the mathematical solution for the one version for which the solution is known and appears to be a reasonable approximation of the solution for the second version of the problem.

Key Words

optimal foraging strategy; genetic programming; genetic algorithms; lizards; crossover

Pages 201-225

Behavior-Based Robot Navigation for Extended Domains

By Ronald C. Arkin

Abstract

Behavior-based robotic systems have been successfully deployed for a wide range of planar ground-based tasks. This article describes how reactive (behavior-based) systems can be applied to new and more difficult target domains. In particular, schema-based navigation is shown to be both feasible and useful in two new areas: three-dimensional navigation for use in aerospace and undersea applications, and "two and one-half"-dimensional surroundings for outdoor navigation in rough terrain. Extensive simulation studies demonstrate the utility of this approach in both cases.

Key Words

reactive control; behavior-based robotics; robot navigation; schema theory

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Adaptive Behavior, 1 (2)

Adaptive Behavior

Volume 1, Number 2

Fall 1992

Table of Contents

J.-P. Ewert, H. Buxbaum-Conradi, S. Fingerling, E. Schürg-Pfeiffer, T. W. Beneke, A. W. Dinges, M. Glagow, and W. W. Schwippert

Adapted and Adaptive Properties in Neural Networks for Visual Pattern Discrimination: A Neurobiological Analysis Toward Neural Engineering