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OpenAI Gym

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하위 태스크: 1
평가표: 17
보존된 평가 기록: 45

An open-source toolkit from OpenAI that implements several Reinforcement Learning benchmarks including: classic control, Atari, Robotics and MuJoCo tasks.

(Description by Evolutionary learning of interpretable decision trees)

(Image Credit: OpenAI Gym)

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/mpatacchiola/imujoco

공식 코드

Comparing the Efficacy of Fine-Tuning and Meta-Learning for Few-Shot Policy Imitation

https://github.com/nekkar/interactive_training

공식 코드

Towards Interactive Training of Non-Player Characters in Video Games

https://github.com/nicolinho/acc

공식 코드

Adaptively Calibrated Critic Estimates for Deep Reinforcement Learning

https://github.com/pemami4911/deep-rl

공식 코드

Deep Reinforcement Learning with Feedback-based Exploration

https://github.com/pikaju/muzero-g

공식 코드

Improving Model-Based Reinforcement Learning with Internal State Representations through Self-Supervision

https://github.com/pseeth/otoworld

공식 코드

OtoWorld: Towards Learning to Separate by Learning to Move

https://github.com/psjanani/RLAProject

공식 코드

Resolving Implicit Coordination in Multi-Agent Deep Reinforcement Learning with Deep Q-Networks & Game Theory

https://github.com/purdue-biorobotics/flappy

공식 코드

Flappy Hummingbird: An Open Source Dynamic Simulation of Flapping Wing Robots and Animals

https://github.com/pyrddlgym-project/pyrddlgym

공식 코드

pyRDDLGym: From RDDL to Gym Environments

https://github.com/qgallouedec/panda-gym

공식 코드

Multi-Goal Reinforcement Learning environments for simulated Franka Emika Panda robot

https://github.com/qutech-delft/qgym

공식 코드

qgym: A Gym for Training and Benchmarking RL-Based Quantum Compilation

https://github.com/rahulkidambi/mobile-neurips2021

공식 코드

MobILE: Model-Based Imitation Learning From Observation Alone

https://github.com/rajcscw/nlp-gym

공식 코드

NLPGym -- A toolkit for evaluating RL agents on Natural Language Processing Tasks

https://github.com/ramp-kits/rl_simulator

공식 코드

Model-based micro-data reinforcement learning: what are the crucial model properties and which model to choose?

https://github.com/rezakakooee/rldesigner

공식 코드

Design Process is a Reinforcement Learning Problem

https://github.com/rickyang2016/bayesian-soft-actor-critic--bsac

공식 코드

Bayesian Soft Actor-Critic: A Directed Acyclic Strategy Graph Based Deep Reinforcement Learning

https://github.com/rl-ina/lemgorl

공식 코드

Towards Real-World Deployment of Reinforcement Learning for Traffic Signal Control

https://github.com/robocin/rSoccer

공식 코드

rSoccer: A Framework for Studying Reinforcement Learning in Small and Very Small Size Robot Soccer

https://github.com/robotology/gym-ignition

공식 코드

Gym-Ignition: Reproducible Robotic Simulations for Reinforcement Learning

https://github.com/roythuly/ompo

공식 코드

OMPO: A Unified Framework for RL under Policy and Dynamics Shifts

https://github.com/rubenrtorrado/GVGAI_GYM

공식 코드

Deep Reinforcement Learning for General Video Game AI

https://github.com/ruizhaogit/mep

공식 코드

Maximum Entropy-Regularized Multi-Goal Reinforcement Learning

https://github.com/saodem74/Transfer-Learning-in-Reinforcement-Learning

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Transfer Reinforcement Learning for Differing Action Spaces via Q-Network Representations

https://github.com/schatty/EMAC

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Solving Continuous Control with Episodic Memory

https://github.com/schuderer/bprl

공식 코드

Sim-Env: Decoupling OpenAI Gym Environments from Simulation Models

https://github.com/scope-lab-vu/PAMCTS

공식 코드

Decision Making in Non-Stationary Environments with Policy-Augmented Search

https://github.com/sensl/andes_gym

공식 코드

Andes_gym: A Versatile Environment for Deep Reinforcement Learning in Power Systems

https://github.com/sfujim/TD3

공식 코드

Addressing Function Approximation Error in Actor-Critic Methods

https://github.com/sfujim/td7

공식 코드

For SALE: State-Action Representation Learning for Deep Reinforcement Learning

https://github.com/shreyassr123/double-sor-q-learning

공식 코드

Double Successive Over-Relaxation Q-Learning with an Extension to Deep Reinforcement Learning

https://github.com/siemens/industrialbenchmark

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A Benchmark Environment Motivated by Industrial Control Problems

https://github.com/siemens/powergym

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PowerGym: A Reinforcement Learning Environment for Volt-Var Control in Power Distribution Systems

https://github.com/sowmya-mp/rl_a3c_pytorch

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Visual Transfer between Atari Games using Competitive Reinforcement Learning

https://github.com/sweety-dm/interference-aware-deep-q-learning

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Catastrophic Interference in Reinforcement Learning: A Solution Based on Context Division and Knowledge Distillation

https://github.com/tavlab-iiitd/VacSIM

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VacSIM: Learning Effective Strategies for COVID-19 Vaccine Distribution using Reinforcement Learning

https://github.com/tgangwani/RL-Indirect-imitation

공식 코드

State-only Imitation with Transition Dynamics Mismatch

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