yubryanj

yubryanj's Stars

• google/jax

  Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

  Language:Python30k3285.5k2.7k

• cbfinn/maml

  Code for "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"

  Language:Python2.6k4778606

• pytorch/rl

  A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

  Language:Python2.4k42640314

• marlbenchmark/on-policy

  This is the official implementation of Multi-Agent PPO (MAPPO).

  Language:Python1.3k894302

• facebookresearch/mbrl-lib

  Library for Model Based RL

  Language:Python9652567157

• hanjuku-kaso/awesome-offline-rl

  An index of algorithms for offline reinforcement learning (offline-rl)

  93345187

• rlworkgroup/metaworld

  An open source robotics benchmark for meta- and multi-task reinforcement learning

  Language:Python81825149182

• google-research/recsim

  A Configurable Recommender Systems Simulation Platform

  Language:Python7483730129

• hijkzzz/pymarl2

  Fine-tuned MARL algorithms on SMAC (100% win rates on most scenarios)

  Language:Python6321740124

• uoe-agents/epymarl

  An extension of the PyMARL codebase that includes additional algorithms and environment support

  Language:Python518762140

• deepmind/meltingpot

  A suite of test scenarios for multi-agent reinforcement learning.

  Language:Python430158280

• marlbenchmark/off-policy

  PyTorch implementations of popular off-policy multi-agent reinforcement learning algorithms, including QMix, VDN, MADDPG, and MATD3.

  Language:Python41531269

• abides-sim/abides

  ABIDES: Agent-Based Interactive Discrete Event Simulation

  Language:Python395180121

• rll-research/url_benchmark

  Language:Python33282652

• gsartoretti/PRIMAL

  PRIMAL: Pathfinding via Reinforcement and Imitation Multi-Agent Learning -- Distributed RL/IL code for Multi-Agent Path Finding (MAPF)

  Language:Python32061378

• xbresson/CS4243_2022

  Computer Vision and Pattern Recognition, NUS CS4243, 2022

  Language:Jupyter Notebook1645026

• forestagostinelli/DeepCubeA

  Code for DeepCubeA, a Deep Reinforcement Learning algorithm that can learn to solve the Rubik's cube.

  Language:Python1624154

• marmotlab/PRIMAL2

  Training code PRIMAL2 - Public Repo

  Language:Python15721559

• facebookresearch/CollaQ

  A code implementation for our arXiv paper "Multi-agent Adhoc Team Play using Decompositional Q function"

  Language:Python12841124

• wjh720/QPLEX

  Language:Python884528

• pvjosue/pytorch_convNd

  Functional N-dimensional convolution in Pytorch, recursively calling convNd until reaching conv3d.

  Language:Python72349

• hijkzzz/noisy-mappo

  Multi-agent PPO with noise (97% win rates on Hard scenarios of SMAC)

  Language:Python54326

• brandontrabucco/design-baselines

  Baselines for Model-Based Optimization

  Language:Python504411

• eli-b/mapf

  A MAPF framework in C#, with implementations for MA-CBS, ICBS, CBSH, ID, A*, A*+OD, and EPEA*

  Language:C#424416

• proroklab/rllib_differentiable_comms

  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.

  Language:Python40323

• xtma/simple-pytorch-rl

  Reinforcement Learning Methods with PyTorch

  Language:Python381314

• ZhengyuLiang24/Conv4d-PyTorch

  Implementation of Conv4d for PyTorch

  Language:Python37214

• facebookresearch/measuring-emergent-comm

  On the pitfalls of measuring emergent communication

  Language:Python34417

• proroklab/adversarial_comms

  Language:Python30364

• asappresearch/emergent-comms-negotiation

  Reproduce ICLR2018 submission "Emergent Communication through Negotiation"

  Language:Python17728