A Robot that Walks: Emergent Behaviors from a Carefully Evolved Network

Most animals have significant behavioral expertise built in without having to explicitly learn it all from scratch. This expertise is a product of evolution of the organism; it can be viewed as a very long term form of learning which provides a structured system within which individuals might...

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Main Author: Brooks, Rodney A.
Language:en_US
Published: 2004
Online Access:http://hdl.handle.net/1721.1/6500
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author Brooks, Rodney A.
author_facet Brooks, Rodney A.
author_sort Brooks, Rodney A.
collection MIT
description Most animals have significant behavioral expertise built in without having to explicitly learn it all from scratch. This expertise is a product of evolution of the organism; it can be viewed as a very long term form of learning which provides a structured system within which individuals might learn more specialized skills or abilities. This paper suggests one possible mechanism for analagous robot evolution by describing a carefully designed series of networks, each one being a strict augmentation of the previous one, which control a six legged walking machine capable of walking over rough terrain and following a person passively sensed in the infrared spectrum. As the completely decentralized networks are augmented, the robot's performance and behavior repertoire demonstrably improve. The rationale for such demonstrations is that they may provide a hint as to the requirements for automatically building massive networks to carry out complex sensory-motor tasks. The experiments with an actual robot ensure that an essence of reality is maintained and that no critical problems have been ignored.
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spelling mit-1721.1/65002019-04-12T08:31:18Z A Robot that Walks: Emergent Behaviors from a Carefully Evolved Network Brooks, Rodney A. Most animals have significant behavioral expertise built in without having to explicitly learn it all from scratch. This expertise is a product of evolution of the organism; it can be viewed as a very long term form of learning which provides a structured system within which individuals might learn more specialized skills or abilities. This paper suggests one possible mechanism for analagous robot evolution by describing a carefully designed series of networks, each one being a strict augmentation of the previous one, which control a six legged walking machine capable of walking over rough terrain and following a person passively sensed in the infrared spectrum. As the completely decentralized networks are augmented, the robot's performance and behavior repertoire demonstrably improve. The rationale for such demonstrations is that they may provide a hint as to the requirements for automatically building massive networks to carry out complex sensory-motor tasks. The experiments with an actual robot ensure that an essence of reality is maintained and that no critical problems have been ignored. 2004-10-04T15:13:06Z 2004-10-04T15:13:06Z 1989-02-01 AIM-1091 http://hdl.handle.net/1721.1/6500 en_US AIM-1091 928752 bytes 655157 bytes application/postscript application/pdf application/postscript application/pdf
spellingShingle Brooks, Rodney A.
A Robot that Walks: Emergent Behaviors from a Carefully Evolved Network
title A Robot that Walks: Emergent Behaviors from a Carefully Evolved Network
title_full A Robot that Walks: Emergent Behaviors from a Carefully Evolved Network
title_fullStr A Robot that Walks: Emergent Behaviors from a Carefully Evolved Network
title_full_unstemmed A Robot that Walks: Emergent Behaviors from a Carefully Evolved Network
title_short A Robot that Walks: Emergent Behaviors from a Carefully Evolved Network
title_sort robot that walks emergent behaviors from a carefully evolved network
url http://hdl.handle.net/1721.1/6500
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