Abstract
This paper describes a method for unfolding a Predicate-net representation of a logistical planning problem, such that it possesses the Markov property. The problem can then be easily converted into a Markov Decision Process (MDP) which can be solved in a tractable manner using standard Dynamic Programming algorithms.
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Naguleswaran, S., Hickmott, S.L., White, L.B. (2005). Reduced MDP Representation of a Logistical Planning Problem Using Petri-Nets. In: Zhang, S., Jarvis, R. (eds) AI 2005: Advances in Artificial Intelligence. AI 2005. Lecture Notes in Computer Science(), vol 3809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11589990_90
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DOI: https://doi.org/10.1007/11589990_90
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30462-3
Online ISBN: 978-3-540-31652-7
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