dunnolab / xland-minigridLinks
JAX-accelerated Meta-Reinforcement Learning Environments Inspired by XLand and MiniGrid 🏎️
☆320Updated 2 weeks ago
Alternatives and similar repositories for xland-minigrid
Users that are interested in xland-minigrid are comparing it to the libraries listed below
Sorting:
- Accelerated minigrid environments with JAX☆154Updated 2 months ago
- ⚡ Flashbax: Accelerated Replay Buffers in JAX☆268Updated 3 months ago
- Data-Driven NetHack Tools: Datasets (30+) and recurrent-baselines (AWAC, BC, CQL, IQL, REM)☆43Updated 2 years ago
- Hardware-Accelerated Reinforcement Learning Algorithms in pure Jax!☆251Updated 2 months ago
- Official Implementation for "In-Context Reinforcement Learning for Variable Action Spaces"☆91Updated last year
- 🏛️A research-friendly codebase for fast experimentation of single-agent reinforcement learning in JAX • End-to-End JAX RL☆378Updated 2 months ago
- XLand-100B: A Large-Scale Multi-Task Dataset for In-Context Reinforcement Learning - - — ICLR 2025☆81Updated 10 months ago
- (Crafter + NetHack) in JAX. ICML 2024 Spotlight.☆360Updated 5 months ago
- Official Implementation for "In-Context Reinforcement Learning from Noise Distillation"☆34Updated last year
- Data-Driven NetHack Tools: Datasets (30+) and recurrent-baselines (AWAC, BC, CQL, IQL, REM)☆76Updated 2 years ago
- High-quality single-file implementations of SOTA Offline and Offline-to-Online RL algorithms: AWAC, BC, CQL, DT, EDAC, IQL, SAC-N, TD3+BC…☆614Updated last year
- Simple single-file baselines for Q-Learning in pure-GPU setting☆229Updated last month
- Single-file SAC-N implementation on jax with flax and equinox. 10x faster than pytorch☆56Updated 2 years ago
- Unified Implementations of Offline Reinforcement Learning Algorithms☆183Updated last week
- ☆90Updated 3 months ago
- Official Implementation of "Can Learned Optimization Make Reinforcement Learning Less Difficult"☆30Updated 2 weeks ago
- Author's implementation of ReBRAC, a minimalist improvement upon TD3+BC☆61Updated 2 years ago
- ☆246Updated last year
- Code for the paper "Showing Your Offline Reinforcement Learning Work: Online Evaluation Budget Matters", ICML 2022☆28Updated 3 years ago
- Challenging Memory-based Deep Reinforcement Learning Agents☆105Updated last year
- ☆89Updated last year
- Partially Observable Process Gym☆209Updated 6 months ago
- Clean single-file implementation of offline RL algorithms in JAX☆163Updated last month
- Benchmarking RL generalization in an interpretable way.☆173Updated last month
- Official implementation for "Anti-Exploration by Random Network Distillation", ICML 2023☆55Updated 2 years ago
- ☆20Updated 7 months ago
- Efficient baselines for autocurricula in JAX.☆205Updated last year
- Accelerated Quality-Diversity☆333Updated 2 months ago
- Simplest and Cleanest DreamerV3 implementation out there☆124Updated 9 months ago
- JAX implementation of RL algorithms and vectorized environments☆50Updated 2 years ago