🔋 Datasets with baselines for offline multi-agent reinforcement learning.
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Updated
Jun 12, 2024 - Python
🔋 Datasets with baselines for offline multi-agent reinforcement learning.
A collection of offline reinforcement learning algorithms.
Summarising the research of Offline RL in Federated Setting.
A Japanese (Riichi) Mahjong AI Framework
📚 List of Top-tier Conference Papers on Reinforcement Learning (RL),including: NeurIPS, ICML, AAAI, IJCAI, AAMAS, ICLR, ICRA, etc.
The source code to Cross-Validated Off-Policy Evaluation
A Production Tool for Embodied AI
Master's Degree Thesis: Applying Reinforcement Learning to Option Pricing and Hedging
Original implementations of the VC-FB and MC-FB algorithms from "Zero-Shot Reinforcement Learning from Low Quality Data" by Jeen et. al (2024).
PyTorch implementation of the Offline Reinforcement Learning algorithm CQL. Includes the versions DQN-CQL and SAC-CQL for discrete and continuous action spaces.
An elegant PyTorch offline reinforcement learning library for researchers.
[NeurIPS 2023] The official implementation of "Offline Multi-Agent Reinforcement Learning with Implicit Global-to-Local Value Regularization"
[ICLR 2024] The official implementation of "Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model"
Robust Offline Reinforcement Learning with Heavy-Tailed Rewards
The Official Code for Offline Model-based Adaptable Policy Learning (NeurIPS'21 & TPAMI)
Code for FOCAL Paper Published at ICLR 2021
The proceedings of top conference in 2018 on the topic of Reinforcement Learning (RL), including: AAAI, IJCAI, NeurIPS, ICML, ICLR, ICRA, AAMAS and more.
The proceedings of top conference in 2019 on the topic of Reinforcement Learning (RL), including: AAAI, IJCAI, NeurIPS, ICML, ICLR, ICRA, AAMAS and more.
The proceedings of top conference in 2020 on the topic of Reinforcement Learning (RL), including: AAAI, IJCAI, NeurIPS, ICML, ICLR, ICRA, AAMAS and more.
[NeurIPS 2023] Counterfactual-Augmented Importance Sampling for Semi-Offline Policy Evaluation. https://arxiv.org/abs/2310.17146
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