J
Jean-François Raskin
Researcher at Université libre de Bruxelles
Publications - 306
Citations - 8087
Jean-François Raskin is an academic researcher from Université libre de Bruxelles. The author has contributed to research in topics: Decidability & Markov decision process. The author has an hindex of 47, co-authored 293 publications receiving 7429 citations. Previous affiliations of Jean-François Raskin include Free University of Brussels & Université de Namur.
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Proceedings Article
Monte Carlo Tree Search Guided by Symbolic Advice for MDPs.
TL;DR: In this paper, symbolic advice is used to bias the selection and simulation strategies of Monte Carlo Tree Search (MCTS) for the online computation of a strategy that aims at optimizing the expected average reward in a Markov decision process.
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Mean-payoff Games with Partial Observation
TL;DR: This paper investigates the algorithmic properties of several subclasses of mean-payoff games where the players have asymmetric information about the state of the game, including a generalization of perfect information games where positional strategies are sufficient.
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{\omega}-Petri nets
TL;DR: It is shown that an {\omega}PN can be turned into an plain Petri net that allows to recover the reachability set of the {\omego}PN, but that does not preserve termination, which yields complexity bounds for the reachable, (place) boundedness and coverability problems on {\omegas}PN.
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Safe Learning for Near Optimal Scheduling
TL;DR: The combination of synthesis techniques and learning techniques to obtain safe and near optimal schedulers for a preemptible task scheduling problem with PAC guarantees and model-free learning techniques based on shielded deep Q-learning are investigated.
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Monte Carlo Tree Search guided by Symbolic Advice for MDPs
TL;DR: The online computation of a strategy that aims at optimizing the expected average reward in a Markov decision process using Monte Carlo tree search and the notion of symbolic advice is considered.