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

, M.Sc. Thesis Sharif University of Technology Jamali, Sima (Author) ; Ghasem Sani, Gholamreza (Supervisor)

Abstract

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...

Using Satisfiability in Solving Planning Problems having Numerical Values

, M.Sc. Thesis Sharif University of Technology Ellahi, Mojtaba (Author) ; Ghasem Sani, Gholamreza (Supervisor)

Abstract

Considering numerical values is an important step toward real world problems in planning. Although planning community has been aware of this fact since many years ago, but the complication involved in reasoning with numerical values made this challenge too difficult, thus very little and occasional research has been done on this issue.This dissertation is an effort to find an efficient method for solving numerical planning problems; in this regard, we use the “planning as satisfiability” approach. Planning as satisfiability is one of the most important and successful approaches for solving planning problems. Furthermore, developing SAT solvers with the capability of considering numerical...

Design and Implementation of a Planning-specific Sat Solver

, M.Sc. Thesis Sharif University of Technology Hamidian Shoormasti, Sina (Author) ; Ghassem-Sani, Gholamreza (Supervisor)

Abstract

Automated planning is a branch of Artificial intelligence aimed at obtaining plans (i.e. sequences of actions) for solving complex problems or for governing the behavior of intelligent agents. Reduction of planning problems to satisfiability problems is one of the most successful approaches to automated planning. In this method first the planning problem with a preset length is coded to a satisfiability problem. Then, a general SAT solver is used for solving the obtained SAT formula. To find the plan with optimum length, plans with increasing coding lengths are evaluated by a SAT solver in a sequential manner. Since much of descriptive information of planning problems is lost in converting...