A Modular Library for Off-Policy Reinforcement Learning with a focus on SafeRL and distributed computing
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Updated
Apr 9, 2024 - Python
A Modular Library for Off-Policy Reinforcement Learning with a focus on SafeRL and distributed computing
PyTorch implementation of D4PG with the SOTA IQN Critic instead of C51. Implementation includes also the extensions Munchausen RL and D2RL which can be added to D4PG to improve its performance.
Distributed PyTorch implementation of D4PG with ray. Using a SOTA IQN Critic instead of C51. Implementation includes also the extensions Munchausen RL and D2RL which can be added to D4PG to improve its performance.
A2C and D4PG implementations for the continuous control challenge. Part of the coursework for Udacity's Deep RL Nanodegree.
Multi-agent reinforcement learning where an agent learns to play tennis against itself. Part of the coursework for Udacity's Deep RL Nanodegree.
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