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 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. A.I. Laboratory Working Papers are produced for internal circulation, and may contain information that is, for example, too preliminary or too detailed for formal publicatidn. It is not intended that they should be considered papers to which reference can be made in the literature.