A. Galuszka and A. Holdyk (Poland)
Artificial intelligence, STRIPS planning, uncertainty, computational efficiency, linear programming
Planning is a difficult computational problem. One way to increase efficiency of searching for a solution may be a transformation of a problem to another problem and then search for a solution of the transformed problem. In this work a transformation of STRIPS planning problem with uncertainty to linear programming is shown. The transformation from planning to Linear Programming is based on mapping of conditions and operators in each plan step to variables. It is proposed to represent the utility function (representing degree of desirability of the plan) using the objective function of linear programming problem. Exemplary simulation shows properties of proposed approach.
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