Multiagent Search Algorithms for Learning & Planning in Colony-Style Robots

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Direct implementation of the sensory-cognitive motor triad for intelligent robotic systems will generally place severe demands on the computing, communication, and memory resources of these systems. One solution to this problem has been to distribute the triad's functionality among various physical components of the robot. The colony-style robot ı1! and its predecessor ı2! (subsummation architecture) represent related methods for achieving this functional distribution. Colony-style robots use a collection(ie., colony) of hierarchically inhibited agents to control the robot. Existing colony-style robots suffer several disadvantages limiting their utility as autonomous system. These disadvantages involve problems in determining the robot's underlying control hierarchy and the inability of existing systems to save and use prior experience. This project uses multiagent processing paradigms called multiagent search strategies of MASS algorithms ı3! to solve the deficiencies of current colony-style systems. MASS algorithms ar inspired by recent work with competitively and cooperatively inhibited neural networks ı3!ı4!. It can be shown, using statistical mechanical arguments, that competitive MASS algorithms can form minimum entropy representations of density functions. This project uses that analytical formalism to develop MASS algorithms capable of learning the components and structure of the colony-style control hierarchy. The research also explores how "cooperative" MASS can be used to realize fully discretized solution of Bellman's dynamic programming equation, and uses this capability to devise a method for implementing long term memory and path planning capabilities in colony-style robots. The project will fully develop, through simulation and analysis, the MASS algorithms needed to realize memory, learning, and planning in colony-style robots. The research will also investigate extensions of this approach to more complex systems such as flexible manufacturing systems.