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GitHub - ElisevanderPol/marl_symmetrizer
May 7th · Contribute to ElisevanderPol/marl_symmetrizer development by creating an account on GitHub.
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ElisevanderPol/mdp-homomorphic-networks
May 7th · Contribute to ElisevanderPol/mdp-homomorphic-networks development by creating an account on GitHub.
Shared by 5, including Matt Shaffer
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Deep Reinforcement Learning Algorithms
Apr 19th · This repository contains most of pytorch implementation based classic deep reinforcement learning algorithms, including - DQN, DDQN, Dueling Network, DDPG, SAC, A2C, PPO, TRPO. (More algorithms are...
Shared by 6, including Matt Shaffer
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sail-sg/envpool: C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.
Apr 19th · C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments. - GitHub - sail-sg/envpool: C++-based high-performance parallel environment execution ...
Shared by 7, including hardmaru, Matt Shaffer
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GitHub - andrew-j-levy/Hierarchical-Actor-Critc-HAC-: This repository contains the code to implement the Hierarchical Actor-Critic (HAC) algorithm.
Apr 19th · This repository contains the code to implement the Hierarchical Actor-Critic (HAC) algorithm. - GitHub - andrew-j-levy/Hierarchical-Actor-Critc-HAC-: This repository contains the code to implement ...
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Xingyu-Lin/VCD: Code for the paper Learning Visible Connectivity Dynamics for Cloth Smoothing
Apr 18th · Code for the paper Learning Visible Connectivity Dynamics for Cloth Smoothing - GitHub - Xingyu-Lin/VCD: Code for the paper Learning Visible Connectivity Dynamics for Cloth Smoothing
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contactrika/dedo: Dynamic Environments with Deformable Objects (DEDO)
Feb 17th · Dynamic Environments with Deformable Objects (DEDO) - GitHub - contactrika/dedo: Dynamic Environments with Deformable Objects (DEDO)
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Yusufma03/CVRL: code for CoRL 2020 paper "Contrastive Variational Model-Based Reinforcement Learning for Complex Observations"
Apr 18th · code for CoRL 2020 paper "Contrastive Variational Model-Based Reinforcement Learning for Complex Observations" - GitHub - Yusufma03/CVRL: code for CoRL 2020 paper "Contrastive Variat...
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iamlab-cmu/isaacgym-utils: Wrappers and utilities for Nvidia IsaacGym
Apr 9th · Wrappers and utilities for Nvidia IsaacGym . Contribute to iamlab-cmu/isaacgym-utils development by creating an account on GitHub.
Shared by 8, including Matt Shaffer
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SerpentAI/SerpentAI
From 2017 · SerpentAI - Game Agent Framework. Helping you create AIs / Bots to play any game you own! BETA
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GitHub - yfletberliac/actor-with-variance-estimated-critic
Apr 4th · AVEC: Actor with Variance Estimated Critic. Contribute to yfletberliac/actor-with-variance-estimated-critic development by creating an account on GitHub.
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GitHub - rlberry-py/rlberry: An easy-to-use reinforcement learning library for research and education.
Apr 4th · An easy-to-use reinforcement learning library for research and education. - GitHub - rlberry-py/rlberry: An easy-to-use reinforcement learning library for research and education.
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tianjunz/MADE
Apr 4th · Contribute to tianjunz/MADE development by creating an account on GitHub.
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flowersteam/TeachMyAgent: TeachMyAgent is a testbed platform for Automatic Curriculum Learning methods in Deep RL.
Apr 4th · TeachMyAgent is a testbed platform for Automatic Curriculum Learning methods in Deep RL. - GitHub - flowersteam/TeachMyAgent: TeachMyAgent is a testbed platform for Automatic Curriculum Learning me...
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facebookresearch/rl: A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
Apr 2nd · A modular, primitive-first, python-first PyTorch library for Reinforcement Learning. - GitHub - facebookresearch/rl: A modular, primitive-first, python-first PyTorch library for Reinforcement Learn...
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GitHub - younggyoseo/RE3: RE3: State Entropy Maximization with Random Encoders for Efficient Exploration
Mar 25th · RE3: State Entropy Maximization with Random Encoders for Efficient Exploration - GitHub - younggyoseo/RE3: RE3: State Entropy Maximization with Random Encoders for Efficient Exploration
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