Discovering state constraints for planning with conditional effects in Discoplan (part I)

Discoplan is a durable and efficient system for inferring state constraints (invariants) in planning domains, specified in the PDDL language. It is exceptional in the range of constraint types it can discover and verify, and it directly allows for conditional effects in action operators. However, although various aspects of Discoplan have been previously described and its utility in planning demonstrated, the underlying methodology, the algorithms for the discovery and inductive verification of constraints, and the proofs of correctness of the algorithms and their complexity analysis have never been laid out in adequate detail. The purpose of this paper is to remedy these lacunae.