Deep Reinforcement Learning codes for study. Currently, there are only codes for algorithms: DQN, C51, QR-DQN, IQN, QUOTA.
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Updated
Mar 15, 2023 - Python
Deep Reinforcement Learning codes for study. Currently, there are only codes for algorithms: DQN, C51, QR-DQN, IQN, QUOTA.
🐳 Implementation of various Distributional Reinforcement Learning Algorithms using TensorFlow2.
[ICRA 2024] Decentralized Multi-Robot Navigation for Autonomous Surface Vehicles with Distributional Reinforcement Learning
[IROS 2023] Robust Unmanned Surface Vehicle Navigation with Distributional Reinforcement Learning
PyTorch implementation of the state-of-the-art distributional reinforcement learning algorithm Fully Parameterized Quantile Function (FQF) and Extensions: N-step Bootstrapping, PER, Noisy Layer, Dueling Networks, and parallelization.
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.
[UR 2023] Robust Route Planning with Distributional Reinforcement Learning in a Stochastic Road Network Environment
Deep reinforcement learning framework for fast prototyping based on PyTorch
Reinforcement learning algorithm implementation
DRL-Router is a method based on distributional reinforcement learning for RSP problem。
Implementation of some of the Deep Distributional Reinforcement Learning Algorithms.
Distributional reinforcement learning algorithm using conjugated discrete distributions (C2D). Data and graphs for stochastic Atari 2600 environments.
Solving CartPole using Distributional RL
[RA-L] Distributional Reinforcement Learning based Integrated Decision Making and Control for Autonomous Surface Vehicles
Author implementation of DSUP(q) algorithms from the NeurIPS 2024 paper "Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning"
Example Categorical DQN implementation with ReLAx
Slide presentation reviewing advances in reinforcement learning
Simple Implementations of RL Algorithm in PyTorch
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