Intelligence As Adaptive Behavior
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Intelligence as Adaptive Behavior
The "intelligence" of traditional artificial intelligence systems is notoriously narrow and inflexible--incapable of adapting to the constantly changing circumstances of the real world. Although traditional artificial intelligence systems can be successful in narrowly prescribed domains, they are inappropriate for dynamic, complex domains, such as autonomous robot navigation.**This book proposes an alternative methodology for designing intelligent systems based on a model of intelligence as adaptive behavior. The author describes an experiment in computational neuroethology--the computer modeling of neuronal control of behavior--in which the nervous system for an artificial insect is modeled. The experiment demonstrates that simple, complete intelligent agents are able to cope with complex, dynamic environments--suggesting that adaptive models of intelligence, based on biological bases of adaptive behavior, may prove to be very useful in the design of intelligent, autonomous systems. - Provides a lucid critique of traditional artificial intelligence research programs - Presents new methodology for the construction autonomous agents, which has implications for mobile robotics - Of interest to researchers in a variety of fields: artificial intelligence, neural networks, robotics, cognitive science, and neuroscience
Adaptive Intelligence
Author: Robert J. Sternberg
language: en
Publisher: Cambridge University Press
Release Date: 2021-02-04
High IQs don't improve the world. Adaptive intelligence does, because it prioritizes the common good over individual success.
Prerational Intelligence: Adaptive Behavior and Intelligent Systems Without Symbols and Logic , Volume 1, Volume 2 Prerational Intelligence: Interdisciplinary Perspectives on the Behavior of Natural and Artificial Systems, Volume 3
Author: Holk Cruse
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-11-11
The present book is the product of conferences held in Bielefeld at the Center for interdisciplinary Sturlies (ZiF) in connection with a year-long ZiF Research Group with the theme "Prerational intelligence". The premise ex plored by the research group is that traditional notions of intelligent behav ior, which form the basis for much work in artificial intelligence and cog nitive science, presuppose many basic capabilities which are not trivial, as more recent work in robotics and neuroscience has shown, and that these capabilities may be best understood as ernerging from interaction and coop eration in systems of simple agents, elements that accept inputs from and act upon their surroundings. The main focus is on the way animals and artificial systems process in formation about their surroundings in order to move and act adaptively. The analysis of the collective properties of systems of interacting agents, how ever, is a problern that occurs repeatedly in many disciplines. Therefore, contributions from a wide variety of areas have been included in order to obtain a broad overview of phenomena that demoostrate complexity arising from simple interactions or can be described as adaptive behavior arising from the collective action of groups of agents. To this end we have invited contributions on topics ranging from the development of complex structures and functions in systems ranging from cellular automata, genetic codes, and neural connectivity to social behavior and evolution. Additional contribu tions discuss traditional concepts of intelligence and adaptive behavior. 1.