proroklab / rllib_differentiable_commsLinks
This is a minimal example to demonstrate how multi-agent reinforcement learning with differentiable communication channels and centralized critics can be realized in RLLib. This example serves as a reference implementation and starting point for making RLLib more compatible with such architectures.
☆43Updated 2 years ago
Alternatives and similar repositories for rllib_differentiable_comms
Users that are interested in rllib_differentiable_comms are comparing it to the libraries listed below
Sorting:
- Benchmarking RL generalization in an interpretable way.☆169Updated 3 weeks ago
- Partially Observable Process Gym☆207Updated 5 months ago
- A tool for aggregating and plotting MARL experiment data.☆80Updated 10 months ago
- Datasets with baselines for Offline MARL.☆191Updated last month
- ☆243Updated last year
- PyTorch implementation of the Option-Critic framework, Harb et al. 2016☆139Updated last year
- PantheonRL is a package for training and testing multi-agent reinforcement learning environments. PantheonRL supports cross-play, fine-tu…☆155Updated 2 years ago
- Fast and flexible multi-agent gridworld reinforcement learning environments.☆46Updated 8 months ago
- IMP-MARL: a Suite of Environments for Large-scale Infrastructure Management Planning via MARL☆45Updated last month
- Level-based Foraging (LBF): A multi-agent environment for RL☆198Updated last year
- Code for Model-Free Opponent Shaping (ICML 2022)☆20Updated 3 years ago
- Author's PyTorch implementation of TD7 for online and offline RL☆154Updated 2 years ago
- Simple (but often Strong) Baselines for POMDPs in PyTorch, ICML 2022☆338Updated last year
- Lightweight multi-agent gridworld Gym environment☆211Updated 2 years ago
- The Starcraft Multi-Agent challenge lite☆42Updated last year
- Implementation of 'RL^2: Fast Reinforcement Learning via Slow Reinforcement Learning'☆71Updated 3 years ago
- Gridworld for MARL experiments☆143Updated 4 years ago
- Conservative Q Learning on top of SAC☆132Updated 3 years ago
- Code for MOPO: Model-based Offline Policy Optimization☆190Updated 3 years ago
- A pytorch reprelication of the model-based reinforcement learning algorithm MBPO☆181Updated 3 years ago
- Datasets for data-driven deep reinforcement learning with Atari (wrapper for datasets released by Google)☆127Updated last year
- Object Centric Atari games☆95Updated last month
- Code and data for the paper "Bridging RL Theory and Practice with the Effective Horizon"☆50Updated last year
- Deep Hierarchical Planning from Pixels☆110Updated 2 years ago
- ☆202Updated 2 years ago
- LAMBDA is a model-based reinforcement learning agent that uses Bayesian world models for safe policy optimization☆38Updated 2 years ago
- JAX and PZ RL envs + algorithms for swarms of CrazyFlies☆85Updated last year
- This code accompanies the paper "Scalable Multi-Agent Model-Based Reinforcement Learning".☆61Updated 8 months ago
- Level-Based Foraging (LBF): A multi-agent reinforcement learning environment☆53Updated last year
- JAX implementation of deep RL agents with resets from the paper "The Primacy Bias in Deep Reinforcement Learning"☆103Updated 3 years ago