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Deep Reinforcement Learning

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코드

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

https://github.com/ihuhuhu/RAC

공식 코드

Balancing Value Underestimation and Overestimation with Realistic Actor-Critic

https://github.com/iitkcpslab/rlstl

공식 코드

STL-Based Synthesis of Feedback Controllers Using Reinforcement Learning

https://github.com/ikostrikov/walk_in_the_park

공식 코드

A Walk in the Park: Learning to Walk in 20 Minutes With Model-Free Reinforcement Learning

https://github.com/illidanlab/Simulator

공식 코드

Efficient Collaborative Multi-Agent Deep Reinforcement Learning for Large-Scale Fleet Management

https://github.com/illidanlab/cdrl

공식 코드

Collaborative Deep Reinforcement Learning

https://github.com/imTurkey/Market-Making-with-Deep-Reinforcement-Learning-from-Limit-Order-Books

공식 코드

Market Making with Deep Reinforcement Learning from Limit Order Books

https://github.com/imatge-upc/detection-2016-nipsws

공식 코드

Hierarchical Object Detection with Deep Reinforcement Learning

https://github.com/imperialcollegelondon/deep_rl_liquidation

공식 코드

Deep Reinforcement Learning for Online Optimal Execution Strategies

https://github.com/innixma/dex

공식 코드

Dex: Incremental Learning for Complex Environments in Deep Reinforcement Learning

https://github.com/insomnia94/ISREG

공식 코드

Iterative Shrinking for Referring Expression Grounding Using Deep Reinforcement Learning

https://github.com/inspirai/wilderness-scavenger

공식 코드

WILD-SCAV: Benchmarking FPS Gaming AI on Unity3D-based Environments

https://github.com/instadeepai/qd-skill-discovery-benchmark

공식 코드

Neuroevolution is a Competitive Alternative to Reinforcement Learning for Skill Discovery

https://github.com/insultedbymaths/6.s890

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Efficient and Scalable Deep Reinforcement Learning for Mean Field Control Games

https://github.com/intelai/cerl

공식 코드

Collaborative Evolutionary Reinforcement Learning

https://github.com/intelligent-control-lab/physicsawarecombinatorialasp

공식 코드

Physics-Aware Combinatorial Assembly Sequence Planning using Data-free Action Masking

https://github.com/inventec-ai-center/carl-siggraph2020

공식 코드

CARL: Controllable Agent with Reinforcement Learning for Quadruped Locomotion

https://github.com/is0383kk/symbolemergence-vae-gmm

공식 코드

Emergent Communication through Metropolis-Hastings Naming Game with Deep Generative Models

https://github.com/isayev/ReLeaSE

공식 코드

Deep Reinforcement Learning for De-Novo Drug Design

https://github.com/isend-clemson/drl-bems

공식 코드

Energy Optimization for HVAC Systems in Multi-VAV Open Offices: A Deep Reinforcement Learning Approach

https://github.com/ishohei220/adopt

공식 코드

ADOPT: Modified Adam Can Converge with Any $β_2$ with the Optimal Rate

https://github.com/ita9naiwa/rlrd-aaai2022

공식 코드

An Efficient Combinatorial Optimization Model Using Learning-to-Rank Distillation

https://github.com/jackieli19/pgportfolio

공식 코드

A Deep Reinforcement Learning Framework For Financial Portfolio Management

https://github.com/jacklinkk/torchgrl

공식 코드

Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffic Environments

https://github.com/jacobandreas/psketch

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Modular Multitask Reinforcement Learning with Policy Sketches

https://github.com/jacooba/hyper

공식 코드

Recurrent Hypernetworks are Surprisingly Strong in Meta-RL

https://github.com/jakub-zarzycki2022/gattaca

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Graph Neural Network-Based Reinforcement Learning for Controlling Biological Networks: The GATTACA Framework

https://github.com/jan-schuchardt/learning-to-evolve

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Learning to Evolve

https://github.com/janisgeise/mb_drl_for_accelerated_learning_from_cfd

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Model-based deep reinforcement learning for accelerated learning from flow simulations

https://github.com/jannkar/doom_actionspace

공식 코드

From Video Game to Real Robot: The Transfer between Action Spaces

https://github.com/janscholten/ppmp

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Deep Reinforcement Learning with Feedback-based Exploration

https://github.com/jaromiru/cwcf

공식 코드

Classification with Costly Features using Deep Reinforcement Learning

https://github.com/jaromiru/nasimemu

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NASimEmu: Network Attack Simulator & Emulator for Training Agents Generalizing to Novel Scenarios

https://github.com/jaromiru/nasimemu-agents

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NASimEmu: Network Attack Simulator & Emulator for Training Agents Generalizing to Novel Scenarios

https://github.com/jaromiru/rcwcf

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Classification with Costly Features in Hierarchical Deep Sets

https://github.com/jaromiru/sr-drl

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Symbolic Relational Deep Reinforcement Learning based on Graph Neural Networks and Autoregressive Policy Decomposition

https://github.com/jayaneetha/Zeta-Policy

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A novel policy for pre-trained Deep Reinforcement Learning for Speech Emotion Recognition

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