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[full paper] |
Antonio Garrido, Derek Long
Purely propositional representation traditionally used to express AI planning problems is not adequate to express numeric variables when modeling real-world continuous resources, such as fuel consumption, energy level, etc. This paper presents a heuristic planning approach that uses a richer representation with capabilities for numeric variables, including duration on actions, and multiobjective optimisation. This approach consists of two stages. First, a spike construction process estimates the values of the variables associated to propositions/actions. Unlike other approaches, we do not relax numeric effects in the calculus of the estimation, but only numeric conditions. Second, a heuristic search process generates a relaxed plan according to the estimations of the first stage, and then performs search in a plan space. The relaxed plan and the heuristic estimations help the process find a plan while trying to optimise the multiobjective criterion.
Keywords: Multiobjective planning, Planning with resources, Temporal planning, Planning
Citation: Antonio Garrido, Derek Long: Planning with Numeric Variables in Multiobjective Planning. In R.López de Mántaras and L.Saitta (eds.): ECAI2004, Proceedings of the 16th European Conference on Artificial Intelligence, IOS Press, Amsterdam, 2004, pp.662-666.