Papers with Code 아카이브

Reinforcement Learning

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

1

평가표

162

보존된 평가 기록

1

코드

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

https://github.com/google-research/robopianist

공식 코드

RoboPianist: Dexterous Piano Playing with Deep Reinforcement Learning

https://github.com/google-research/seed_rl

공식 코드

SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference

https://github.com/google-research/tf-opt

공식 코드

Reinforcement Learning with Combinatorial Actions: An Application to Vehicle Routing

https://github.com/google-research/valan

공식 코드

VALAN: Vision and Language Agent Navigation

https://github.com/google/brain_autorl

공식 코드

Evolving Reinforcement Learning Algorithms

https://github.com/google/brain_autorl/tree/main/evolving_rl

공식 코드

Evolving Reinforcement Learning Algorithms

https://github.com/google/dopamine

공식 코드

Deep Reinforcement Learning

https://github.com/google/intelligent_annotation_dialogs

공식 코드

Learning Intelligent Dialogs for Bounding Box Annotation

https://github.com/gorkamunoz/rl_opts

공식 코드

Optimal foraging strategies can be learned

https://github.com/gp1g/fedaa

공식 코드

FedAA: A Reinforcement Learning Perspective on Adaptive Aggregation for Fair and Robust Federated Learning

https://github.com/gpdwatkins/graph_colouring_with_RL

공식 코드

Generating a Graph Colouring Heuristic with Deep Q-Learning and Graph Neural Networks

https://github.com/gpoesia/socratic-tutor

공식 코드

Contrastive Reinforcement Learning of Symbolic Reasoning Domains

https://github.com/gpt4vision/r1-sgg

공식 코드

Compile Scene Graphs with Reinforcement Learning

https://github.com/graal-research/shallow-planning-partial-observability

공식 코드

On shallow planning under partial observability

https://github.com/gracefulning/mec_morl_multipolicy

공식 코드

Multi-objective Deep Reinforcement Learning for Mobile Edge Computing

https://github.com/greydanus/visualize_atari

공식 코드

Visualizing and Understanding Atari Agents

https://github.com/grimmlab/drl4procsyn

공식 코드

Deep reinforcement learning uncovers processes for separating azeotropic mixtures without prior knowledge

https://github.com/grockious/deepsynth

공식 코드

DeepSynth: Automata Synthesis for Automatic Task Segmentation in Deep Reinforcement Learning

https://github.com/grockious/lcrl

공식 코드

Logically-Constrained Reinforcement Learning

https://github.com/gsastry/human-rl

공식 코드

Trial without Error: Towards Safe Reinforcement Learning via Human Intervention

https://github.com/gsoumyajit/Finite-Horizon-with-constraints

공식 코드

A policy gradient approach for Finite Horizon Constrained Markov Decision Processes

https://github.com/gt-star-lab/constrained-rl-dexterous-manipulation

공식 코드

Constrained Reinforcement Learning for Dexterous Manipulation

https://github.com/guetye/dhrl-fnmr

공식 코드

DHRL-FNMR: An Intelligent Multicast Routing Approach Based on Deep Hierarchical Reinforcement Learning in SDN

https://github.com/guetye/drl-pponsa

공식 코드

An Intelligent SDWN Routing Algorithm Based on Network Situational Awareness and Deep Reinforcement Learning

https://github.com/guiliang/cirl-benchmarks-public

공식 코드

Benchmarking Constraint Inference in Inverse Reinforcement Learning

https://github.com/guiliang/icrl-benchmarks-public

공식 코드

Benchmarking Constraint Inference in Inverse Reinforcement Learning

https://github.com/gundoganalperen/DIRAL

공식 코드

Distributed Resource Allocation with Multi-Agent Deep Reinforcement Learning for 5G-V2V Communication

https://github.com/gunshi/offline_active_rl

공식 코드

Can Active Sampling Reduce Causal Confusion in Offline Reinforcement Learning?

https://github.com/guojm14/ESPL

공식 코드

Efficient Symbolic Policy Learning with Differentiable Symbolic Expression

https://github.com/guojyjy/avars

공식 코드

AVARS -- Alleviating Unexpected Urban Road Traffic Congestion using UAVs

https://github.com/guojyjy/cotv

공식 코드

CoTV: Cooperative Control for Traffic Light Signals and Connected Autonomous Vehicles using Deep Reinforcement Learning

https://github.com/guolingbing/rlea

공식 코드

Deep Reinforcement Learning for Entity Alignment

https://github.com/guoyihonggyh/mobody-model-based-off-dynamics-offline-reinforcement-learning

공식 코드

MOBODY: Model Based Off-Dynamics Offline Reinforcement Learning

https://github.com/guoyongcs/NAT

공식 코드

NAT: Neural Architecture Transformer for Accurate and Compact Architectures

https://github.com/guozheng-ma/da-in-visualrl

공식 코드

A Comprehensive Survey of Data Augmentation in Visual Reinforcement Learning

https://github.com/guytenn/terminator

공식 코드

Reinforcement Learning with a Terminator

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.