TAIPE: tactical assistants for interaction planning and execution
AGENTS '97 Proceedings of the first international conference on Autonomous agents
An explicit semantics for coordination multiagent plan execution
An explicit semantics for coordination multiagent plan execution
Readings in agents
Decision-making in an embedded reasoning system
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
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Agents for real applications often operate in complex, dynamic, and nondeterministic environments and thus need to function in worlds with exogenous events, other agents, and uncertain effects. In this paper, we present our reactive agent view to describe agents for real-world applications and introduce our two agent architectures: UMPRS and Jam. UM-PRS has been applied to both physical robots and software agents and demonstrated its sufficiently powerful representation and control scheme as a general reactive agent architecture. The Jam agent architecture has evolved from UM-PRS and implemented in Java for maximum portability and mobility. We first identify agent tasks and environments and then highlight the relevant features in our agent architectures.