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Improving the Efficiency of Sat-Based Planning by Enhancing the Representations

Jamali, Sima | 2014

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 47010 (19)
  4. University: Sharif University of Technology
  5. Department: Computer Engineering
  6. Advisor(s): Ghasem Sani, Gholamreza
  7. Abstract:
  8. Automated planning is a branch of artiticial intelligence that studies intelligent agents’ decision making process. The objective is to design agents that are able to decide on their own, about how to perform tasks that are assigned to them. In the past 20 years, a popular and appealing method for solving planning problems has been to use satisfiability (SAT) techniques. In this method, the planning ptoblem with a preset length would be encoded into a satisfiability problem, which is then solved by a general satisfiability solver. The solution to the planning problem is then extracted from the solution of the SAT problem. The length of the problem is proportional to the number of steps in the produced plan. One of the biggest drawbacks of this approach, considering time and space constraint, is the enormous size of the formulae that is generated by the proposed encoding. In this dissertation, we try to reduce the size of this formulae by decreasing the number of steps needed to solve the given problems. Two methods are proposed. The first one is a classical version of the encoding used in the ITSAT planner, which is a temporal planner. In this method, the encoding let more than one action to be placed in one step. The second method is a preprocessing technique that orders the actions in a way where more actions can be placed in a single step. The proposed methods have been implemented in a planner named C-SATPLAN. Comparison between C-SATPLAN and the best relevant planners shows a significant improvement made by the proposed methods
  9. Keywords:
  10. Classical Planning ; Satisfiability ; Satisfiability-based Planning ; Artificial Intelligence Planning

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