5 citations · 8 across the 11 of their papers we have counts for
5 papers · 1 filter
Automata with Timers
Véronique Bruyère, Guillermo A. Pérez, Gaëtan Staquet +1
In this work, we study properties of deterministic finite-state automata with timers, a subclass of timed automata proposed by Vaandrager et al. as a candidate for an efficiently l…
Graph-Based Reductions for Parametric and Weighted MDPs
Kasper Engelen, Guillermo A. Pérez, Shrisha Rao
We study the complexity of reductions for weighted reachability in parametric Markov decision processes. That is, we say a state p is never worse than q if for all valuations of th…
Bi-Objective Lexicographic Optimization in Markov Decision Processes with Related Objectives
Damien Busatto-Gaston, Debraj Chakraborty, Anirban Majumdar +3
We consider lexicographic bi-objective problems on Markov Decision Processes (MDPs), where we optimize one objective while guaranteeing optimality of another. We propose a two-stag…
Wasserstein Auto-encoded MDPs: Formal Verification of Efficiently Distilled RL Policies with Many-sided Guarantees
Florent Delgrange, Ann Nowé, Guillermo A. Pérez
Although deep reinforcement learning (DRL) has many success stories, the large-scale deployment of policies learned through these advanced techniques in safety-critical scenarios i…
The Wasserstein Believer: Learning Belief Updates for Partially Observable Environments through Reliable Latent Space Models
Raphael Avalos, Florent Delgrange, Ann Nowé +2
Partially Observable Markov Decision Processes (POMDPs) are used to model environments where the full state cannot be perceived by an agent. As such the agent needs to reason takin…