A relevance-based compilation method for Conformant probabilistic planning Conference Paper uri icon

abstract

  • Conformant probabilistic planning (CPP) differs from conformant planning (CP) by two key elements: the initial belief state is probabilistic, and the conformant plan must achieve the goal with probability≥ θ, for some 0< θ≤ 1. In earlier work we observed that one can reduce CPP to CP by finding a set of initial states whose probability≥ θ, for which a conformant plan exists. In previous solvers we used the underlying planner to select this set of states and to plan for them simultaneously. Here we suggest an alternative approach: start with relevance analysis to determine a promising set of initial states on which to focus. Then, call an off-the- shelf conformant planner to solve the resulting problem. This approach has a number of advantages. First, instead of depending on the heuristic function to select the set of initial states, we can introduce specific, efficient relevance reasoning techniques. Second, we …

publication date

  • January 1, 2014