pseudo-rnd-thoughts

pseudo-rnd-thoughts's Stars

• huggingface/lerobot

  🤗 LeRobot: Making AI for Robotics more accessible with end-to-end learning

  Language:Python8.2k84166840

• arcee-ai/mergekit

  Tools for merging pretrained large language models.

  Language:Python5.1k54335474

• chrxh/alien

  ALIEN is a CUDA-powered artificial life simulation program.

  Language:C++5k5782159

• facebookresearch/sapiens

  High-resolution models for human tasks.

  Language:Python4.7k46173270

• danijar/dreamerv3

  Mastering Diverse Domains through World Models

  Language:Python1.5k28144240

• younader/Vesuvius-Grandprize-Winner

  Language:Python59712240

• oTree-org/oTree

  Python framework for multiplayer decision games, behavioral experiments, and surveys

  Language:Python4723669200

• salesforce/warp-drive

  Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning Framework on a GPU (JMLR 2022)

  Language:Python468153678

• ndif-team/nnsight

  The nnsight package enables interpreting and manipulating the internals of deep learned models.

  Language:Jupyter Notebook45749241

• nicklashansen/tdmpc2

  Code for "TD-MPC2: Scalable, Robust World Models for Continuous Control"

  Language:Python42864499

• google-deepmind/treescope

  An interactive HTML pretty-printer for machine learning research in IPython notebooks.

  Language:Python37081619

• proroklab/VectorizedMultiAgentSimulator

  VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.

  Language:Python36596072

• EdanToledo/Stoix

  🏛️A research-friendly codebase for fast experimentation of single-agent reinforcement learning in JAX • End-to-End JAX RL

  Language:Python26273326

• zuoxingdong/mazelab

  A customizable framework to create maze and gridworld environments

  Language:Python2609959

• Emerge-Lab/gpudrive

  GPU-acceleration of Nocturne via Madrona

  Language:Jupyter Notebook24655720

• imbue-ai/carbs

  Cost aware hyperparameter tuning algorithm

  Language:Jupyter Notebook1369613

• mttga/purejaxql

  Simple single-file baselines for Q-Learning in pure-GPU setting

  Language:Python132107

• epignatelli/navix

  Accelerated minigrid environments with JAX

  Language:Python12733211

• Farama-Foundation/momaland

  Benchmarks for Multi-Objective Multi-Agent Decision Making

  Language:Python755815

• adityab/CrossQ

  Official code release for "CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity"

  Language:Python63484

• k4ntz/OC_Atari

  Object Centric Atari games

  Language:Python608211

• BricksRL/bricksrl

  BricksRL: A Platform for Democratizing Robotics and Reinforcement Learning Research and Education with LEGO

  Language:Python54102

• strakam/generals-bots

  Develop your agent for generals.io!

  Language:Python383136

• nikaashpuri/sarfa-saliency

  Language:C++34436

• smearle/autoverse

  Generative cellular automaton-like learning environments for RL.

  Language:Python19300

• brownirl/lambda_discrepancy

  Mitigating Partial Observability in Sequential Decision Processes via the Lambda Discrepancy

  Language:Python17100

• dadecampo/aquatic_navigation_envs

  Aquatic navigation environments for Gym

  Language:ASP.NET16200

• adaptive-intelligent-robotics/QDAC

  Repository for "Quality-Diversity Actor-Critic: Learning High-Performing and Diverse Behaviors via Value and Successor Features Critics" (ICML 2024).

  Language:Python12301

• k4ntz/HackAtari

  Language:Python12614

• smearle/pcgrl-jax

  Language:Python9204