1 citations · 1 across the 18 of their papers we have counts for
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Learning a Ranking from Human Feedback in Log-Concave Random Utility Models
Diego Alovisetti, Marco Mussi, Alberto Maria Metelli
We study the problem of recovering the ranking of a fixed set of items according to their unknown numerical utilities. At each interaction with the environment, a learner presents…
Reusing Past Samples in Proximal Policy Optimization: When and How Does It Help?
Alessandro Montenegro, Riccardo Venturelli, Marco Mussi +2
Among on-policy deep reinforcement learning methods, Proximal Policy Optimization (PPO) has become the de facto standard, due to its consistently strong empirical performance acros…
On Generalizing Preference-based Reinforcement Learning to Multi-Objective Problems
Simone Drago, Marco Mussi, Leonardo Bianconi +1
We study reinforcement learning (RL) from pairwise human-generated trajectory comparisons. We generalize preference-based RL by formalizing a novel setting in which the expert can…