Planning and Scheduling in Hybrid Domains Using Answer Set Programming
This addresses planning and scheduling challenges in hybrid domains for AI researchers, but it appears incremental as it builds on existing methods like action language H and A-Prolog.
The paper tackles planning and scheduling problems in hybrid domains with discrete and continuous behavior by using an Action Language-Answer Set Programming approach, reducing these problems to computing answer sets of A-Prolog programs and demonstrating applicability with a hybrid solver.
In this paper we present an Action Language-Answer Set Programming based approach to solving planning and scheduling problems in hybrid domains - domains that exhibit both discrete and continuous behavior. We use action language H to represent the domain and then translate the resulting theory into an A-Prolog program. In this way, we reduce the problem of finding solutions to planning and scheduling problems to computing answer sets of A-Prolog programs. We cite a planning and scheduling example from the literature and show how to model it in H. We show how to translate the resulting H theory into an equivalent A-Prolog program. We compute the answer sets of the resulting program using a hybrid solver called EZCSP which loosely integrates a constraint solver with an answer set solver. The solver allows us reason about constraints over reals and compute solutions to complex planning and scheduling problems. Results have shown that our approach can be applied to any planning and scheduling problem in hybrid domains.