Generation of Strong Cyclic Plans with Incomplete Information and Sensing
Luca Iocchi, Daniele Nardi, Riccardo Rosati · 2004
Incomplete information and sensing are needed in order to design agents that operate in domains where their information acquisition capabilities are restricted and the environment may evolve in unpredictable ways. These representation issues, that have been studied by the work on reasoning about actions, are also being addressed from a planning perspective. The aim of this paper is to present a language for expressing planning domains with incomplete knowledge and sensing and by providing a new technique for generating cyclic plans under partial observability in such a framework.