The Automated Mapping of Plans for Plan Recognition

To coordinate with other agents in its environment, an agent needs models of what the other agents are trying to do. When communication is impossible or expensive, this information must be acquired indirectly via plan recognition. Typical approaches to plan recognition start with a speci cation of the possible plansthe other agents maybe following, and develop special techniques for discriminating among the possibilities. Perhaps more desirable would be a uniformprocedure for mapping plans to general structures supporting inference based on uncertain and incomplete observations. In this paper, we describe a set of methods for converting plans represented in a exible procedural language to observation models represented as probabilistic belief networks.

• Type: Conference
• Year: 1994
• Where: AAAI
• Authors: Marcus J. Huber, Edmund H. Durfee, Michael P. Wellman
• Keywords: AAAI 1994, Agent Needs Models, Intelligent Agents, Plan Recognition, Structures Supporting Inference