Regression with Respect to Sensing Actions and Partial States

Le-Chi Tuan, Chitta Baral, Xin Zhang, and Tran Cao Son

In this paper, we present a state-based regression function for planning domains where an agent does not have complete information and may have sensing actions. We consider binary domains 1, and employ the 0-approximation to define the regression function. In binary domains, the use of 0-approximation means using 3-valued states. Although planning using this approach is incomplete with respect to the full semantics, we adopt it to have a lower complexity. We prove the soundness and completeness of our regression formulation with respect to the definition of progression and develop a conditional planner that utilizes our regression function.


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