Critical Analysis of Programming in Societies of Behaviors

Programming in societies of behavior-agents is emerging as a promising method for creating mobile robot control systems that are responsive both to internal priorities for action and to external world constraints. It is essentially a new approach to finding modularities in real-time control systems...

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Main Author: Cudhea, Peter
Format: Working Paper
Language:en_US
Published: MIT Artificial Intelligence Laboratory 2008
Online Access:http://hdl.handle.net/1721.1/41172
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author Cudhea, Peter
author_facet Cudhea, Peter
author_sort Cudhea, Peter
collection MIT
description Programming in societies of behavior-agents is emerging as a promising method for creating mobile robot control systems that are responsive both to internal priorities for action and to external world constraints. It is essentially a new approach to finding modularities in real-time control systems in which module boundaries are sought not between separate information processing functions, but between separate task-achieving units. Task achieving units for complex behaviors are created by merging together the task-achieving units from simpler component behaviors into societies with competing and cooperating parts. This paper surveys the areas of agreement and disagreement in four approaches to programming with societies of behaviors. By analyzing where the systems differ, both on what constitutes a task-achieving unit and on how to merge such units together, this paper hopes to lay the groundwork for future work on controlling robust mobile robots using this approach.
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spelling mit-1721.1/411722019-04-10T22:36:33Z Critical Analysis of Programming in Societies of Behaviors Cudhea, Peter Programming in societies of behavior-agents is emerging as a promising method for creating mobile robot control systems that are responsive both to internal priorities for action and to external world constraints. It is essentially a new approach to finding modularities in real-time control systems in which module boundaries are sought not between separate information processing functions, but between separate task-achieving units. Task achieving units for complex behaviors are created by merging together the task-achieving units from simpler component behaviors into societies with competing and cooperating parts. This paper surveys the areas of agreement and disagreement in four approaches to programming with societies of behaviors. By analyzing where the systems differ, both on what constitutes a task-achieving unit and on how to merge such units together, this paper hopes to lay the groundwork for future work on controlling robust mobile robots using this approach. MIT Artificial Intelligence Laboratory 2008-04-15T13:26:56Z 2008-04-15T13:26:56Z 1986-12 Working Paper http://hdl.handle.net/1721.1/41172 en_US MIT Artificial Intelligence Laboratory Working Papers, WP-291 application/pdf MIT Artificial Intelligence Laboratory
spellingShingle Cudhea, Peter
Critical Analysis of Programming in Societies of Behaviors
title Critical Analysis of Programming in Societies of Behaviors
title_full Critical Analysis of Programming in Societies of Behaviors
title_fullStr Critical Analysis of Programming in Societies of Behaviors
title_full_unstemmed Critical Analysis of Programming in Societies of Behaviors
title_short Critical Analysis of Programming in Societies of Behaviors
title_sort critical analysis of programming in societies of behaviors
url http://hdl.handle.net/1721.1/41172
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