Practical reasoning and automated planning are strictly related as they strive to answer to the same question: “which is the best course of action for an agent?” While the first research field addressed this topic mainly from an epistemological point of view, automated planning dealt with this question for the most partfrom a heuristic or reasoning perspective. In this position paper we want to discuss the improvements
in terms of computational complexity of algorithms, and of knowledge representation and reasoning power on complex planning problems, which can be derived by applying practical reasoning techniques to planning problems. In particular, we sketch how argumentation-based structures for practical reasoning may help for improving the computational complexity of a state-of-the-art approach in optimal planning.
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