Determining redundant actions in sequential plans

Automated planning even in its simplest form, classical planning, is a computationally hard problem. With the increasing involvement of intelligent systems in everyday life there is a need for more and more advanced planning techniques able to solve planning problems in little (or real) time. However, planners designed to solve planning problems as fast as possible often provide solution plans of low quality. The quality of solution plans can be improved by their post-planning analysis by which redundant actions or optimizable sub plans can be identified. In this paper, we present techniques for determining redundancy of actions in plans. Especially, we present techniques for efficient redundancy checking of pairs of inverse actions. These techniques are accompanied with necessary theoretical foundations and are also empirically evaluated using existing planning systems and standard planning benchmarks.