Trace Equivalence Characterization Through Reinforcement Learning

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 PACguarantees on this estimation.

• Type: Conference
• Year: 2006
• Where: AI
• Authors: Josee Desharnais, François Laviolette, Krishna Priya Darsini Moturu, Sami Zhioua
• Keywords: AI 2006, Artificial Intelligence, Labelled Markov Processes, Particular Derived Markov, Trace-equivalence Divergence