3 citations · 7 across the 12 of their papers we have counts for
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Can You Trust Your Preference Models? Stackelberg Games for Alignment
Riccardo Formenti, Aditya Agrawal, Vikas Garg
Language models are frequently aligned to human preferences via imperfect evaluators whose errors can be exploited during optimization. We train policies to search for comparisons…
Adaptive Policy Portfolios for Robust Markov Decision Processes
Kasper Engelen, Sebastian Junges, Guillermo A. Pérez +1
Robust Markov decision processes optimize one policy against a set of plausible transition functions. This can be conservative when the unknown dynamics are fixed and become partia…
On the Complexity of Robust Markov Decision Processes and Bisimulation Metrics
Marnix Suilen, Guillermo A. Pérez
Robust Markov decision processes (RMDPs) extend standard Markov decision processes (MDPs) to account for uncertainty in the transition probabilities. RMDPs have an uncertainty set…