Trace Equivalence Characterization Through Reinforcement Learning
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- Desharnais J., Laviolette F., Moturu K.P.D., Zhioua S. (2006) Trace Equivalence Characterization Through Reinforcement Learning. In: Lamontagne L., Marchand M. (eds) Advances in Artificial Intelligence. AI 2006. Lecture Notes in Computer Science, vol 4013. Springer, Berlin, Heidelberg
In the context of probabilistic verification, we provide a new notion of trace-equivalence divergence between pairs of Labelled Markov processes. This divergence corresponds to the optimal value of a particular derived Markov Decision Process. It can therefore be estimated by Reinforcement Learning methods. Moreover, we provide some PAC-guarantees on this estimation.
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