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 1721–1730 of 15113 papers

Title	Date	Tasks	Status	Hype
Few-Shot Complex Knowledge Base Question Answering via Meta Reinforcement Learning	Oct 29, 2020	Knowledge Base Question AnsweringMeta Reinforcement Learning	CodeCode Available	1
Recovery RL: Safe Reinforcement Learning with Learned Recovery Zones	Oct 29, 2020	Contact-rich Manipulationreinforcement-learning	CodeCode Available	1
Succinct and Robust Multi-Agent Communication With Temporal Message Control	Oct 27, 2020	Multi-agent Reinforcement LearningReinforcement Learning (RL)	CodeCode Available	1
COG: Connecting New Skills to Past Experience with Offline Reinforcement Learning	Oct 27, 2020	reinforcement-learningReinforcement Learning (RL)	CodeCode Available	1
Learning Financial Asset-Specific Trading Rules via Deep Reinforcement Learning	Oct 27, 2020	Deep Reinforcement Learningreinforcement-learning	CodeCode Available	1
Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning	Oct 27, 2020	Deep Reinforcement Learningreinforcement-learning	CodeCode Available	1
MELD: Meta-Reinforcement Learning from Images via Latent State Models	Oct 26, 2020	Meta-LearningMeta Reinforcement Learning	CodeCode Available	1
Personalised Meta-path Generation for Heterogeneous GNNs	Oct 26, 2020	Deep Reinforcement LearningGraph Representation Learning	CodeCode Available	1
Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning	Oct 26, 2020	ClusteringModel-based Reinforcement Learning	CodeCode Available	1
Multi-UAV Path Planning for Wireless Data Harvesting with Deep Reinforcement Learning	Oct 23, 2020	Collision AvoidanceDeep Reinforcement Learning	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