SOTAVerified

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

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Showing 10301–10325 of 15113 papers

TitleStatusHype
A Sharp Analysis of Model-based Reinforcement Learning with Self-Play—0
Test-Cost Sensitive Methods for Identifying Nearby Points—0
Mean-Variance Efficient Reinforcement Learning with Applications to Dynamic Financial Investment—0
Disentangling causal effects for hierarchical reinforcement learning—0
Attractor Selection in Nonlinear Energy Harvesting Using Deep Reinforcement Learning—0
Beyond Tabula-Rasa: a Modular Reinforcement Learning Approach for Physically Embedded 3D Sokoban—0
Interactive Reinforcement Learning for Feature Selection with Decision Tree in the Loop—0
MADRaS : Multi Agent Driving Simulator—0
Reinforcement Learning of Sequential Price Mechanisms—0
Multi-Reward based Reinforcement Learning for Neural Machine Translation—0
Emergent Social Learning via Multi-agent Reinforcement Learning—0
Student-Initiated Action Advising via Advice NoveltyCode0
Nearly Minimax Optimal Reinforcement Learning for Discounted MDPs—0
Bayesian Meta-reinforcement Learning for Traffic Signal Control—0
Recognition Method of Important Words in Korean Text based on Reinforcement Learning—0
Deep Reinforcement Learning with Mixed Convolutional Network—0
Bridging the gap between Markowitz planning and deep reinforcement learning—0
Finding It at Another Side: A Viewpoint-Adapted Matching Encoder for Change Captioning—0
Deep Reinforcement Learning for Efficient Measurement of Quantum DevicesCode0
Accelerating Optimization and Reinforcement Learning with Quasi-Stochastic Approximation—0
Graph-based Heuristic Search for Module Selection Procedure in Neural Module Network—0
AAMDRL: Augmented Asset Management with Deep Reinforcement Learning—0
Entropy Regularization for Mean Field Games with Learning—0
Toolpath design for additive manufacturing using deep reinforcement learning—0
Teacher-Critical Training Strategies for Image Captioning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PPGMean Normalized Performance0.76—Unverified
2PPOMean Normalized Performance0.58—Unverified