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Reinforcement Learning and Automated Planning: A Survey
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Author(s): Ioannis Partalas (Aristotle University of Thessaloniki, Greece), Dimitris Vrakas (Aristotle University of Thessaloniki, Greece)and Ioannis Vlahavas (Aristotle University of Thessaloniki, Greece)
Copyright: 2008
Pages: 18
Source title:
Artificial Intelligence for Advanced Problem Solving Techniques
Source Author(s)/Editor(s): Ioannis Vlahavas (Aristotle University, Greece)and Dimitris Vrakas (Aristotle University, Greece)
DOI: 10.4018/978-1-59904-705-8.ch006
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Abstract
This article presents a detailed survey on Artificial Intelligent approaches, that combine Reinforcement Learning and Automated Planning. There is a close relationship between those two areas as they both deal with the process of guiding an agent, situated in a dynamic environment, in order to achieve a set of predefined goals. Therefore, it is straightforward to integrate learning and planning, in a single guiding mechanism and there have been many approaches in this direction during the past years. The approaches are organized and presented according to various characteristics, as the used planning mechanism or the reinforcement learning algorithm.
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