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 1751–1760 of 15113 papers

Title	Date	Tasks	Status	Hype
Knowledge Transfer in Multi-Task Deep Reinforcement Learning for Continuous Control	Oct 15, 2020	continuous-controlContinuous Control	CodeCode Available	1
A game-theoretic analysis of networked system control for common-pool resource management using multi-agent reinforcement learning	Oct 15, 2020	ManagementMulti-agent Reinforcement Learning	CodeCode Available	1
Constrained Model-based Reinforcement Learning with Robust Cross-Entropy Method	Oct 15, 2020	Model-based Reinforcement LearningModel Predictive Control	CodeCode Available	1
Masked Contrastive Representation Learning for Reinforcement Learning	Oct 15, 2020	Atari GamesContrastive Learning	CodeCode Available	1
Modeling Protagonist Emotions for Emotion-Aware Storytelling	Oct 14, 2020	reinforcement-learningReinforcement Learning (RL)	CodeCode Available	1
UAV Path Planning using Global and Local Map Information with Deep Reinforcement Learning	Oct 14, 2020	Deep Reinforcement Learningreinforcement-learning	CodeCode Available	1
Deep Reinforcement Learning for Real-Time Optimization of Pumps in Water Distribution Systems	Oct 13, 2020	Deep Reinforcement Learningreinforcement-learning	CodeCode Available	1
Measuring Visual Generalization in Continuous Control from Pixels	Oct 13, 2020	continuous-controlContinuous Control	CodeCode Available	1
Efficient Wasserstein Natural Gradients for Reinforcement Learning	Oct 12, 2020	Policy Gradient Methodsreinforcement-learning	CodeCode Available	1
Distributed Resource Allocation with Multi-Agent Deep Reinforcement Learning for 5G-V2V Communication	Oct 11, 2020	Deep Reinforcement LearningDistributed Optimization	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