The model-based approach to autonomous behavior: Prospects and challenges

Article type: Research Article

Authors: Geffner, Hector

Affiliations: ICREA & DTIC Universitat Pompeu Fabra, c/Roc Boronat 138, 55.213, 08018 Barcelona, Spain E-mail: [email protected]

Abstract: The selection of the action to do next is one of the central problems faced by autonomous agents. In AI, three approaches have been used to address this problem: the programming-based approach, where the agent controller is given by the programmer, the learning-based approach, where the controller is induced from experience via a learning algorithm, and the model-based approach, where the controller is derived from a model of the problem. Planning in AI is best conceived as the model-based approach to action selection. The models represent the initial situation, actions, sensors, and goals. A main challenge in planning is computational, as all the models, whether accommodating feedback and uncertainty or not, are intractable in the worst case. In this article, I review some of the models considered in current planning research, the progress achieved in solving these models, and some open problems.

Keywords: Planning, autonomous behavior, control synthesis

DOI: 10.3233/IA-2011-0024

Journal: Intelligenza Artificiale, vol. 5, no. 2, pp. 163-169, 2011