Distillation of RL Policies with Formal Guarantees via Variational Abstraction of Markov Decision Processes

Tue, 28 Jun 2022 00:00:00 +0000

VAE-MDPs

Fri, 17 Dec 2021 00:00:00 +0000

A TensorFlow 2 implementation of Variational Markov Decision Processes, a framework allowing to (i) distill policies learned through (deep) reinforcement learning and (ii) learn discrete abstractions of continuous environments, the two with bisimulation guarantees.

The source code provided allows replicating the experiments presented in the paper Distillation of RL Policies with Formal Guarantees via Variational Abstraction of Markov Decision Processes.

The source code is available on GitHub.

Variational Autoencoders | Florent Delgrange

Distillation of RL Policies with Formal Guarantees via Variational Abstraction of Markov Decision Processes

VAE-MDPs