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 4076–4100 of 15113 papers

TitleStatusHype
Offline Policy Optimization in RL with Variance Regularizaton—0
Towards automating Codenames spymasters with deep reinforcement learning—0
On the Convergence of Discounted Policy Gradient Methods—0
Certifying Safety in Reinforcement Learning under Adversarial Perturbation Attacks—0
Improving a sequence-to-sequence nlp model using a reinforcement learning policy algorithm—0
Don't do it: Safer Reinforcement Learning With Rule-based Guidance—0
Lexicographic Multi-Objective Reinforcement LearningCode1
Towards Learning Abstractions via Reinforcement Learning—0
Representation Learning in Deep RL via Discrete Information Bottleneck—0
Offline Reinforcement Learning via Linear-Programming with Error-Bound Induced Constraints—0
On Pathologies in KL-Regularized Reinforcement Learning from Expert DemonstrationsCode1
Model-Based Reinforcement Learning with Multinomial Logistic Function Approximation—0
Optimal scheduling of island integrated energy systems considering multi-uncertainties and hydrothermal simultaneous transmission: A deep reinforcement learning approach—0
Strangeness-driven Exploration in Multi-Agent Reinforcement LearningCode0
Data-driven control of COVID-19 in buildings: a reinforcement-learning approach—0
Learning Generalizable Representations for Reinforcement Learning via Adaptive Meta-learner of Behavioral SimilaritiesCode0
Off-Policy Reinforcement Learning with Loss Function Weighted by Temporal Difference Error—0
Novel Reinforcement Learning Algorithm for Suppressing Synchronization in Closed Loop Deep Brain Stimulators—0
Streaming Traffic Flow Prediction Based on Continuous Reinforcement Learning—0
Understanding the Complexity Gains of Single-Task RL with a Curriculum—0
SHIRO: Soft Hierarchical Reinforcement Learning—0
Automated Gadget Discovery in ScienceCode0
Deep Reinforcement Learning for Heat Pump Control—0
Example-guided learning of stochastic human driving policies using deep reinforcement learningCode1
Offline Reinforcement Learning for Human-Guided Human-Machine Interaction with Private Information—0
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Benchmark Results

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