Structured plans and observation reduction for plans with contexts

Authors:
Wei Huang;Zhonghua Wen;Yunfei Jiang;Hong Peng
Affiliations:
School of Computer Science & Engineering, South China University of Technology, Guangzhou, China;College of Information Engineering, Xiangtan University, Xiangtan, China;Software Research Institute, School of Information Science and Technology, Sun Yat-sen University, Guangzhou, China;School of Computer Science & Engineering, South China University of Technology, Guangzhou, China
Venue:
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Year:
2009

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Abstract

In many real world planning domains, some observation information is optional and useless to the execution of a plan; on the other hand, information acquisition may require some kind of cost. The problem of observation reduction for strong plans has been addressed in the literature. However, observation reduction for plans with contexts (which are more general and useful than strong plans in robotics) is still a open problem. In this paper, we present an attempt to solve the problem. Our first contribution is the definition of structured plans, which can encode sequential, conditional and iterative behaviors, and is expressive enough for dealing with incomplete observation information and internal states of the agent. A second contribution is an observation reduction algorithm for plans with contexts, which can transform a plan with contexts into a structured plan that only branches on necessary observation information.