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Towards Optimal Cooperative Path Planning in Hard Setups through Satisfiability Solving

  • Pavel Surynek
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7458)

Abstract

A novel approach to cooperative path-planning is presented. A SAT solver is used not to solve the whole instance but for optimizing the makespan of a sub-optimal solution. This approach is trying to exploit the ability of stateof- the-art SAT solvers to give a solution to relatively small instance quickly. A sub-optimal solution to the instance is obtained by some existent method first. It is then submitted to the optimization process which decomposes it into small subsequences for which optimal solutions are found by a SAT solver. The new shorter solution is subsequently obtained as concatenation of optimal subsolutions. The process is iterated until a fixed point is reached. This is the first method to produce near optimal solutions for densely populated environments; it can be also applied to domain-independent planning supposed that suboptimal planner is available.

Keywords

Base Solution Primitive Action Inverse Location Populated Environment Cooperative Path 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Pavel Surynek
    • 1
    • 2
  1. 1.Faculty of Mathematics and PhysicsCharles University in PraguePraha 1Czech Republic
  2. 2.Graduate School of Maritime Sciences, Intelligent Informatics LaboratoryKobe UniversityKobeJapan

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