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03/22/2023
Wasserstein Auto-encoded MDPs: Formal Verification of Efficiently Distilled RL Policies with Many-sided Guarantees
Although deep reinforcement learning (DRL) has many success stories, the...
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03/06/2023
The Wasserstein Believer: Learning Belief Updates for Partially Observable Environments through Reliable Latent Space Models
Partially Observable Markov Decision Processes (POMDPs) are useful tools...
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12/17/2021
Distillation of RL Policies with Formal Guarantees via Variational Abstraction of Markov Decision Processes (Technical Report)
We consider the challenge of policy simplification and verification in t...
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10/24/2019
Simple Strategies in Multi-Objective MDPs (Technical Report)
We consider the verification of multiple expected reward objectives at o...
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01/11/2019
