https://github.com/google/deluca
공식 코드Deluca -- A Differentiable Control Library: Environments, Methods, and Benchmarking
Papers with Code 아카이브
OpenAI Gym
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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/haarnoja/sac
공식 코드Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
https://github.com/hardmaru/astool
공식 코드https://github.com/heiner/scalable_agent
공식 코드https://github.com/herolab-uga/bsac
공식 코드Bayesian Soft Actor-Critic: A Directed Acyclic Strategy Graph Based Deep Reinforcement Learning
https://github.com/himat/CHAPtER
공식 코드https://github.com/illidanlab/cdrl
공식 코드https://github.com/inpefess/basic-rl-prover
공식 코드Project proposal: A modular reinforcement learning based automated theorem prover
https://github.com/intelligent-environments-lab/CityLearn
공식 코드https://github.com/jackyk02/distributed_rl_benchmarks
공식 코드Efficient Parallel Reinforcement Learning Framework using the Reactor Model
https://github.com/jacr13/maad
공식 코드Mimicking Better by Matching the Approximate Action Distribution
https://github.com/janscholten/ppmp
공식 코드https://github.com/jaraujo98/SinglePartitionAdaptiveQLearning
공식 코드https://github.com/joelferguson/underactuated_mechanical_cbi
공식 코드Total energy-shaping control for mechanical systems via Control-by-Interconnection
https://github.com/jpmorganchase/abides-jpmc-public
공식 코드https://github.com/jtbish/ppsn2020
공식 코드Optimality-based Analysis of XCSF Compaction in Discrete Reinforcement Learning
https://github.com/juhgiyo/ude
공식 코드https://github.com/kailashg26/swiftrl
공식 코드SwiftRL: Towards Efficient Reinforcement Learning on Real Processing-In-Memory Systems
https://github.com/kakaoenterprise/jorldy
공식 코드JORLDY: a fully customizable open source framework for reinforcement learning
https://github.com/kengz/SLM-Lab
공식 코드https://github.com/kramerlab/peerlearning
공식 코드Peer Learning: Learning Complex Policies in Groups from Scratch via Action Recommendations
https://github.com/kzl/decision-transformer
공식 코드Decision Transformer: Reinforcement Learning via Sequence Modeling
https://github.com/leozhengzly/stackelberg-actor-critic-algos
공식 코드Stackelberg Actor-Critic: Game-Theoretic Reinforcement Learning Algorithms
https://github.com/lisaoakley/flipit-simulation
공식 코드QFlip: An Adaptive Reinforcement Learning Strategy for the FlipIt Security Game
https://github.com/lisaoakley/gym-flipit
공식 코드QFlip: An Adaptive Reinforcement Learning Strategy for the FlipIt Security Game
https://github.com/mail-ecnu/text-gym-agents
공식 코드Can language agents be alternatives to PPO? A Preliminary Empirical Study On OpenAI Gym
https://github.com/mario-holubar/RacingRL
공식 코드Continuous-action Reinforcement Learning for Playing Racing Games: Comparing SPG to PPO
https://github.com/marko-vasic/moet
공식 코드MoËT: Mixture of Expert Trees and its Application to Verifiable Reinforcement Learning
https://github.com/maximilienlc/gane
공식 코드Generative Adversarial Neuroevolution for Control Behaviour Imitation
https://github.com/maximilienlc/nra
공식 코드https://github.com/meowatthemoon/decisionmamba
공식 코드https://github.com/meowatthemoon/hierarchicaldecisionmamba
공식 코드https://github.com/mfranzs/meta-learning-curiosity-algorithms
공식 코드https://github.com/michael-beukman/waveletrl
공식 코드https://github.com/mingyucai/Modular_Deep_RL_E-LDGBA
공식 코드Modular Deep Reinforcement Learning for Continuous Motion Planning with Temporal Logic
https://github.com/montrealrobotics/dal
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.