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Diff4RLSurvey
This repository contains a collection of resources and papers on Diffusion Models for RL, accompanying the paper "Diffusion Models for Reinforcement Learning: A Survey"Imitation-Learning-Paper-Lists
Paper Collection for Imitation Learning in RL.Batch-Offline--RL-Paper-Lists
Paper Collection for Batch RL with brief introductions.GCRL-Collection
This repo relates to the survey paper <Goal-Conditioned Reinforcement Learning: Problems and Solutions>. We collects widely used benchmark environments and conclude a series of research works for goal-conditioned reinforcement learning (GCRL).RL-Exploration-Paper-Lists
Paper Collection of Reinforcement Learning Exploration covers Exploration of Muti-Arm-Bandit, Reinforcement Learning and Multi-agent Reinforcement Learning.bmpo
Implementation of ICML2020 paper <Bidirectional Model-based Policy Optimization>QSnakeGame
Snake game RL environment for Ubiquant competition 2022.CoDAIL
Implementation of CoDAIL in the ICLR 2020 paper <Multi-Agent Interactions Modeling with Correlated Policies>COIL
Code for NeurIPS 2021 paper "Curriculum Offline Imitation Learning"AORPO
Official pytorch implementation of the paper <Model-based Multi-agent Policy Optimization with Adaptive Opponent-wise Rollouts>.autombpo
Implementation of NeurIPS2021 paper <On Effective Scheduling of Model-based Reinforcement Learning>EBIL-torch
Pytorch Implementation of AAMAS 2021 paper <Energy-Based Imitation Learning>Reinforcement-Learning-Platforms
Collections of powerful RL architectures with brief introductions.DePO
Code for ICML 2022 paper "Plan Your Target and Learn Your Skills: Transferable State-Only Imitation Learning via Decoupled Policy Optimization"MapGo
TensorFlow implementation of the IJCAI 2021 paper MapGo: Model-Assisted Policy Optimization for Goal-Oriented TasksDePO_NGSIM
Code for ICML 2021 paper "Plan Your Target and Learn Your Skills: Transferable State-Only Imitation Learning via Decoupled Policy Optimization" on NGSIM datasetRL2S
Implementation of the ECML-PKDD 2021 paper "Learning to Build High-fidelity and Robust Environment Models"Love Open Source and this site? Check out how you can help us