staghuntrpg / RPG
This is the source code of RPG (Reward-Randomized Policy Gradient)
☆43Updated 2 years ago
Related projects: ⓘ
- Codes accompanying the paper "Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning" (NeurIPS…☆69Updated last year
- Source code for the paper "Divergence-Augmented Policy Optimization"☆37Updated 4 years ago
- ☆53Updated 6 months ago
- A new paper list for multi-agent reinforcement learning (actively maintained)☆25Updated 4 years ago
- Code for "Multi-task Reinforcement Learning with Soft Modularization"☆108Updated 3 years ago
- PyTorch IMPALA implementation☆24Updated 5 years ago
- ☆21Updated 2 years ago
- ☆44Updated last year
- Code accompanying the paper "TiZero: Mastering Multi-Agent Football with Curriculum Learning and Self-Play" (AAMAS 2023) 足球游戏智能体☆47Updated last year
- ☆103Updated last year
- Implementation of ICML2020 paper <Bidirectional Model-based Policy Optimization>☆23Updated last year
- [ICLR 2022 Spotlight] Code for Reinforcement Learning with Sparse Rewards using Guidance from Offline Demonstration☆26Updated 2 years ago
- Code for NeurIPS 2021 paper "Curriculum Offline Imitation Learning"☆17Updated last year
- Generalized Decision Transformer for Offline Hindsight Information Matching (ICLR2022)☆64Updated 2 years ago
- CaDM: Context-aware Dynamics Model for Generalization in Model-based Reinforcement Learning☆63Updated 4 years ago
- Related papers for offline reforcement learning (we mainly focus on representation and sequence modeling and conventional offline RL)☆17Updated 2 years ago
- Code for "Offline Meta-Reinforcement Learning with Advantage Weighting" [ICML 2021]☆45Updated last year
- Official PyTorch implementation of "Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble" (NeurIPS'21)☆68Updated 2 years ago
- Learning Invariant Representations for Reinforcement Learning without Reconstruction☆142Updated 3 years ago
- Code for FOCAL Paper Published at ICLR 2021☆49Updated 9 months ago
- ☆115Updated last month
- [ICML 2021] DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning☆29Updated last year
- ☆35Updated 2 years ago
- Maximum Entropy Population Based Training for Zero-Shot Human-AI Coordination☆25Updated last year
- Codes accompanying the paper "DOP: Off-Policy Multi-Agent Decomposed Policy Gradients" (ICLR 2021, https://arxiv.org/abs/2007.12322)☆51Updated last year
- A code implementation for our arXiv paper "Multi-agent Adhoc Team Play using Decompositional Q function"☆127Updated last year
- Code for Mildly Conservative Q-learning for Offline Reinforcement Learning (NeurIPS 2022)☆49Updated 4 months ago
- Code from the paper "Effective Diversity in Population Based Reinforcement Learning", presented as a spotlight at NeurIPS 2020. This is t…☆44Updated 3 years ago
- Learning Action-Value Gradients in Model-based Policy Optimization☆31Updated 3 years ago
- Benchmarked implementations of Offline RL Algorithms.☆62Updated 4 months ago