Papers with Code 아카이브

Reinforcement Learning

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코드

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

https://github.com/yingchengyang/CPPO

공식 코드

Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk

https://github.com/yingchengyang/Two-Stage-Attack

공식 코드

Understanding Adversarial Attacks on Observations in Deep Reinforcement Learning

https://github.com/yingfan-bot/mbpsrl

공식 코드

Model-based Reinforcement Learning for Continuous Control with Posterior Sampling

https://github.com/yinglunxu/reward_poisoning_attack_drl

공식 코드

Efficient Reward Poisoning Attacks on Online Deep Reinforcement Learning

https://github.com/yinxusen/learning_to_generalize

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Learning to Generalize for Sequential Decision Making

https://github.com/yiwenai/opentensor

공식 코드

OpenTensor: Reproducing Faster Matrix Multiplication Discovering Algorithms

https://github.com/yiwenlu66/learning-qp

공식 코드

MPC-Inspired Reinforcement Learning for Verifiable Model-Free Control

https://github.com/yix8/visualplanning

공식 코드

Visual Planning: Let's Think Only with Images

https://github.com/yjwang0618/subgoal-based-exploration

공식 코드

Dynamic Subgoal-based Exploration via Bayesian Optimization

https://github.com/yk7333/drnd

공식 코드

Exploration and Anti-Exploration with Distributional Random Network Distillation

https://github.com/yk7333/taskallocation

공식 코드

A Two-stage Reinforcement Learning-based Approach for Multi-entity Task Allocation

https://github.com/ymollard/APEX

공식 코드

Intrinsically Motivated Goal Exploration Processes with Automatic Curriculum Learning

https://github.com/ymzhang01/focops

공식 코드

First Order Constrained Optimization in Policy Space

https://github.com/yoavalon/MultiQuadcopterReinforcmentLearning

공식 코드

Multi-Agent Reinforcement Learning for Unmanned Aerial Vehicle Coordination by Multi-Critic Policy Gradient Optimization

https://github.com/yobibyte/atarigrandchallenge

공식 코드

The Atari Grand Challenge Dataset

https://github.com/yohannnchen/afst

공식 코드

Reinforcement Learning for Robot Navigation with Adaptive Forward Simulation Time (AFST) in a Semi-Markov Model

https://github.com/yokian/distspectrl

공식 코드

DistSPECTRL: Distributing Specifications in Multi-Agent Reinforcement Learning Systems

https://github.com/yooceii/Rotation-Translation-and-Cropping-for-Zero-Shot-Generalization

공식 코드

Rotation, Translation, and Cropping for Zero-Shot Generalization

https://github.com/yotamitai/coviz

공식 코드

Explaining Reinforcement Learning Agents Through Counterfactual Action Outcomes

https://github.com/younggyoseo/apv

공식 코드

Reinforcement Learning with Action-Free Pre-Training from Videos

https://github.com/youpengzhao/crashed_agent

공식 코드

Coach-assisted Multi-Agent Reinforcement Learning Framework for Unexpected Crashed Agents

https://github.com/ysaikai/rlir

공식 코드

Deep reinforcement learning for irrigation scheduling using high-dimensional sensor feedback

https://github.com/ysmei97/mac-po

공식 코드

MAC-PO: Multi-Agent Experience Replay via Collective Priority Optimization

https://github.com/yuanhangzhang98/ml_quantum_compiling

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Topological Quantum Compiling with Reinforcement Learning

https://github.com/yuanmingqi/adept

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Adaptive Data Exploitation in Deep Reinforcement Learning

https://github.com/yuanmu97/mlink

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MLink: Linking Black-Box Models from Multiple Domains for Collaborative Inference

https://github.com/yudasong/briee

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Provable Benefits of Representational Transfer in Reinforcement Learning

https://github.com/yuedongP/BanditSum

공식 코드

BanditSum: Extractive Summarization as a Contextual Bandit

https://github.com/yueeeeeeee/hrpo

공식 코드

Hybrid Latent Reasoning via Reinforcement Learning

https://github.com/yuelin301/informationdesignmarl

공식 코드

Information Design in Multi-Agent Reinforcement Learning

https://github.com/yuezhu95/intelligent-traffic-light-via-reinforcement-learning

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Intelligent Traffic Light via Policy-based Deep Reinforcement Learning

https://github.com/yufeiwang63/ROLL

공식 코드

ROLL: Visual Self-Supervised Reinforcement Learning with Object Reasoning

https://github.com/yufengyuan/ur5_async_rl

공식 코드

Asynchronous Reinforcement Learning for Real-Time Control of Physical Robots

https://github.com/yuguangyue/CARSM

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Discrete Action On-Policy Learning with Action-Value Critic

https://github.com/yuhui15/multi-preference-lambda-weighted-dpo

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Multi-Preference Lambda-weighted Listwise DPO for Dynamic Preference Alignment

https://github.com/yujizou/llrp

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A reinforcement learning guided hybrid evolutionary algorithm for the latency location routing problem

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