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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 13501–13550 of 15113 papers

TitleStatusHype
A Reinforcement Learning Framework for Natural Question Generation using Bi-discriminators—0
Neural Math Word Problem Solver with Reinforcement Learning—0
Structured Dialogue Policy with Graph Neural Networks—0
Multi-Agent Deep Reinforcement Learning for Dynamic Power Allocation in Wireless NetworksCode0
Learning Dexterous In-Hand Manipulation—0
Count-Based Exploration with the Successor RepresentationCode0
Learning to Interrupt: A Hierarchical Deep Reinforcement Learning Framework for Efficient Exploration—0
Improving Spatiotemporal Self-Supervision by Deep Reinforcement Learning—0
Optimal Tap Setting of Voltage Regulation Transformers Using Batch Reinforcement Learning—0
Multi-Agent Generative Adversarial Imitation LearningCode1
Multi-modal Feedback for Affordance-driven Interactive Reinforcement Learning—0
A Reinforcement Learning Approach to Target Tracking in a Camera Network—0
Backprop-Q: Generalized Backpropagation for Stochastic Computation GraphsCode0
Multi-Agent Reinforcement Learning: A Report on Challenges and ApproachesCode0
Variational Bayesian Reinforcement Learning with Regret Bounds—0
A Temporal Difference Reinforcement Learning Theory of Emotion: unifying emotion, cognition and adaptive behavior—0
Learning to Play Pong using Policy Gradient Learning—0
Contrastive Explanations for Reinforcement Learning in terms of Expected Consequences—0
Accelerated Structure-Aware Reinforcement Learning for Delay-Sensitive Energy Harvesting Wireless Sensors—0
Asynchronous Advantage Actor-Critic Agent for Starcraft II—0
NAVREN-RL: Learning to fly in real environment via end-to-end deep reinforcement learning using monocular images—0
Learning Heuristics for Quantified Boolean Formulas through Deep Reinforcement LearningCode0
Hierarchical Reinforcement Learning for Zero-shot Generalization with Subtask DependenciesCode0
FuzzerGym: A Competitive Framework for Fuzzing and Learning—0
Towards Explainable and Controllable Open Domain Dialogue Generation with Dialogue Acts—0
Self-Organizing Maps as a Storage and Transfer Mechanism in Reinforcement Learning—0
Representational efficiency outweighs action efficiency in human program induction—0
News-based trading strategies—0
Backplay: "Man muss immer umkehren"Code0
Learning to Listen, Read, and Follow: Score Following as a Reinforcement Learning GameCode0
Deep Reinforcement Learning for Swarm SystemsCode0
Foundations for Restraining Bolts: Reinforcement Learning with LTLf/LDLf restraining specifications—0
Remember and Forget for Experience ReplayCode0
Safe Reinforcement Learning via Probabilistic Shields—0
Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees—0
Online Robust Policy Learning in the Presence of Unknown Adversaries—0
Discrete linear-complexity reinforcement learning in continuous action spaces for Q-learning algorithms—0
Bipedal Walking Robot using Deep Deterministic Policy GradientCode0
Exploring Hierarchy-Aware Inverse Reinforcement Learning—0
An Affective Robot Companion for Assisting the Elderly in a Cognitive Game Scenario—0
Visual Reinforcement Learning with Imagined GoalsCode2
The Bottleneck Simulator: A Model-based Deep Reinforcement Learning Approach—0
Will it Blend? Composing Value Functions in Reinforcement Learning—0
Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical GuaranteesCode0
CIRL: Controllable Imitative Reinforcement Learning for Vision-based Self-driving—0
Is Q-learning Provably Efficient?Code1
Partial Policy-based Reinforcement Learning for Anatomical Landmark Localization in 3D Medical Images—0
Video Summarisation by Classification with Deep Reinforcement Learning—0
Auto Deep Compression by Reinforcement Learning Based Actor-Critic Structure—0
Financial Trading as a Game: A Deep Reinforcement Learning ApproachCode0
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Benchmark Results

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