Abstract
In this paper, we introduce an approach called RTBSS (Real-Time Belief Space Search) for real-time decision making in large POMDPs. The approach is based on a look-ahead search that is applied online each time the agent has to make a decision. RTBSS is particularly interesting for large real-time environments where offline solutions are not applicable because of their complexity.
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Paquet, S., Tobin, L., Chaib-draa, B. (2005). Real-Time Decision Making for Large POMDPs. In: Kégl, B., Lapalme, G. (eds) Advances in Artificial Intelligence. Canadian AI 2005. Lecture Notes in Computer Science(), vol 3501. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11424918_49
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DOI: https://doi.org/10.1007/11424918_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25864-3
Online ISBN: 978-3-540-31952-8
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