Desire-space analysis and action selection for multiple dynamic goals

Authors:
David C. Han;K. Suzanne Barber
Affiliations:
The Laboratory for Intelligent Processes and Systems, Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX;The Laboratory for Intelligent Processes and Systems, Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX
Venue:
CLIMA'04 Proceedings of the 5th international conference on Computational Logic in Multi-Agent Systems
Year:
2004

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Abstract

Autonomous agents are given the authority to select which actions they will execute. If the agent behaves rationally, the actions it selects will be in its own best interests. When addressing multiple goals, the rational action may not be obvious. Equipping the agents with decision-theoretic methods allows the agent to mathematically evaluate the risks, uncertainty, and benefits of the various available courses of action. Using this evaluation, an agent can determine which goals are worth achieving, as well as the order in which to achieve those goals. When the goals of the agent changes, the agent must replan to maintain rational decision-making. This research uses macro actions to transform the state space for the agent's decision problem into the desire space of the agent. Reasoning in the desire space, the agent can efficiently maintain rationality in response to addition and removal of goals.