Parallelism and Fault Tolerance in the Design of Distributed Intelligent Agents for Robotic Control

Abstract One of the most exciting and challenging research areas in our modern world involves the design and implementation of intelligent agents. In this paper we outline the specifications for applying recent advances in parallel processing and distributed computing technology to the design and analysis of parallel algorithms associated with the creation of the clusters necessary for the efficient operation of distributed intelligent agents. Intelligent agents, whose application spans the spectrum from internal combustion engines to remote robotic control, must be able to make decisions, act autonomously, and exhibit real time behavior in a potentially hostile environment. Recent advances in parallel processing including fault tolerance in programming languages provides an arena in which to explore and apply this technology to the construction of robotic systems that exhibit decision making capability and respond in real time