4 papers
A Survey on the Verification of Reinforcement Learning Policies
Luca Marzari, Ezio Bartocci, Enrico Marchesini
Reinforcement learning (RL) is increasingly applied in complex, safety-critical domains, yet the lack of rigorous behavioral guarantees for neural network-based policies remains a…
Probabilistic Verification of Recurrent Neural Networks for Single and Multi-Agent Reinforcement Learning
Luca Marzari, Enrico Marchesini
History-dependent policies induced by recurrent neural networks (RNNs) rely on latent hidden state dynamics, making verification in partially observable reinforcement learning (RL)…
RL2Grid: Benchmarking Reinforcement Learning in Power Grid Operations
Enrico Marchesini, Benjamin Donnot, Constance Crozier +7
Reinforcement learning (RL) can provide adaptive and scalable controllers essential for power grid decarbonization. However, RL methods struggle with power grids' complex dynamics,…
Improving Policy Optimization via -Retrain
Luca Marzari, Priya L. Donti, Changliu Liu +1
We present -retrain, an exploration strategy encouraging a behavioral preference while optimizing policies with monotonic improvement guarantees. To this end, we intro…