Regression With Respect to Sensing Actions and Partial States.

Chitta Baral, Le-Chi Tuan, Xin Zhang and Tran 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 both binary and non-binary domains, and employ the 0-approximation \cite{SB01} 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, we adopt it to have a lower complexity. We prove the soundness of our regression formulation with respect to the definition of progression and develop a conditional planner that utilizes our regression function. Preliminary experimental results indicate that our planner outperforms other planners with similar capability in well-known planning domains from the literature.