PIPSS*: A System based on Temporal Estimates

Conference paper


AI planning and scheduling are two closely related areas. Planning provides a set of actions that achieves a set of goals, and scheduling assigns time and resources to the actions. Currently, most of the real world problems require the use of shared and limited resources with time constraints when planning. Then, systems that can integrate planning and scheduling techniques to deal with this kind of problems are needed.

This paper describes the extension performed in PIPSS (Parallel Integration Planning and Scheduling System) called PIPSS*. PIPSS combines traditional state space heuristic search planning with constraint satisfaction algorithms. The extension is based on heuristic functions that allows the planner to reduce the search space based on time estimations that imposes temporal constraints to the scheduler. The purpose is to achieve a tighter integration respect to the previous version and minimize the makespan. Results show that PIPSS* outperforms state of the art planners under the temporal satisficing track in the IPC-08 competition for the tested domains.


Planning Graph Schedule System Heuristic Function Temporal Network Schedule Technique 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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This work has been founded by the Junta de Comunidades de Castilla-La Mancha project PEII09-0266-6640.


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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  1. 1.Departamento de AutomáticaUniversidad de AlcaláMadridSpain

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