Compact Policies for Fully-Observable Non-Deterministic Planning as SAT
This work addresses the need for efficient policy computation in FOND planning, which is incremental as it builds on existing SAT-based methods with variations for different planning types.
The authors tackled the problem of generating compact policies for fully observable non-deterministic (FOND) planning by introducing a SAT encoding that produces compact strong cyclic policies, with empirical comparisons showing competitive performance against existing planners on benchmarks.
Fully observable non-deterministic (FOND) planning is becoming increasingly important as an approach for computing proper policies in probabilistic planning, extended temporal plans in LTL planning, and general plans in generalized planning. In this work, we introduce a SAT encoding for FOND planning that is compact and can produce compact strong cyclic policies. Simple variations of the encodings are also introduced for strong planning and for what we call, dual FOND planning, where some non-deterministic actions are assumed to be fair (e.g., probabilistic) and others unfair (e.g., adversarial). The resulting FOND planners are compared empirically with existing planners over existing and new benchmarks. The notion of "probabilistic interesting problems" is also revisited to yield a more comprehensive picture of the strengths and limitations of current FOND planners and the proposed SAT approach.