IPSS: A Problem Solver that Integrates Planning and Scheduling

M. D. R-Moreno, D. Borrajo, A. Oddi, A. Cesta, and D. Meziat

In Proceedings of the 3rd Italian Workshop on Planning and Scheduling, AI*IA Symposium, Perugia, Italy, September, 2004

Recently the fields of AI planning and scheduling have witnessed a big interest on the integration of techniques from both areas in order to solve complex problems. These problems require the reasoning on which actions to be performed as well as their precedence constrains (planning) in combination with the reasoning with respect to the time at which those actions should be executed and the resources they use (scheduling). In this paper we describe IPSS (Integrated Planning and Scheduling System) a domain independent solver that integrates an AI heuristic planner, that synthesizes courses of actions, with constraint satisfaction (CS) techniques that reason about time and resources. IPSS is able to reason about precedence constraints, time (deadline, time windows, etc) and binary resource usage/consumption. Experimental results show that the contextual reasoning of the planner with the CSP solver allows to improve the total makespan on a set of problems characterized by multiple agents. The results show that the time and resource reasoning also allow to regain plan parallelism that is not preserved by the planner.