This paper presents a new architecture for controlling autonomous agents in dynamic multi-agent worlds, building on previous work addressing reactive and deliberative control methods. The proposed multi-layered architecture allows a rationally bounded, goal-directed agent to reason predictively about potential conflicts by constructing causal theories which explain other agents’ observed behaviors and hypothesize their intentions; at the same time it enables the agent to operate autonomously and to react promptly to changes in its real-time environment. A principal aim of this research is to understand the role different functional capabilities play in constraining an agent’s behavior under varying environmental conditions. To this end, an experimental testbed has been constructed comprising a simulated multi-agent world in which a variety of agent configurations and behaviors have been investigated. A number of experimental findings are reported.
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