Reinforcement Learning (RL)

Reinforcement Learning (RL) involves training an agent to take actions in an environment to maximize a cumulative reward signal. The agent interacts with the environment and learns by receiving feedback in the form of rewards or punishments for its actions. The goal of reinforcement learning is to find the optimal policy or decision-making strategy that maximizes the long-term reward.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 471–480 of 15113 papers

Title	Date	Tasks	Status	Hype
Curriculum Offline Imitation Learning	Nov 3, 2021	continuous-controlContinuous Control	CodeCode Available	1
Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation	Oct 18, 2022	Domain Adaptationreinforcement-learning	CodeCode Available	1
Contrastive Retrospection: honing in on critical steps for rapid learning and generalization in RL	Oct 12, 2022	Contrastive LearningOut-of-Distribution Generalization	CodeCode Available	1
Distributed Multi-Agent Reinforcement Learning with One-hop Neighbors and Compute Straggler Mitigation	Feb 18, 2022	Distributed ComputingMulti-agent Reinforcement Learning	CodeCode Available	1
Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement Learning	Jul 29, 2022	Contrastive LearningDeep Reinforcement Learning	CodeCode Available	1
DataLight: Offline Data-Driven Traffic Signal Control	Mar 20, 2023	Offline RLReinforcement Learning (RL)	CodeCode Available	1
Contrastive Preference Learning: Learning from Human Feedback without RL	Oct 20, 2023	reinforcement-learningReinforcement Learning (RL)	CodeCode Available	1
A Closer Look at Advantage-Filtered Behavioral Cloning in High-Noise Datasets	Oct 10, 2021	Decision Makingreinforcement-learning	CodeCode Available	1
Contrastive Reinforcement Learning of Symbolic Reasoning Domains	Jun 16, 2021	reinforcement-learningReinforcement Learning	CodeCode Available	1
Contrastive Variational Reinforcement Learning for Complex Observations	Aug 6, 2020	Atari GamesContinuous Control	CodeCode Available	1

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Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	PPG	Mean Normalized Performance	0.76	—	Unverified
2	PPO	Mean Normalized Performance	0.58	—	Unverified