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 14201–14250 of 15113 papers

TitleStatusHype
Transferring Agent Behaviors from Videos via Motion GANs—0
Posterior Sampling for Large Scale Reinforcement Learning—0
Teaching a Machine to Read Maps with Deep Reinforcement LearningCode0
Deep Reinforcement Learning for Multi-Resource Multi-Machine Job Scheduling—0
Classification with Costly Features using Deep Reinforcement LearningCode0
Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement LearningCode0
Neural Network Based Reinforcement Learning for Audio-Visual Gaze Control in Human-Robot Interaction—0
Run, skeleton, run: skeletal model in a physics-based simulationCode0
Hindsight policy gradientsCode0
Finding Efficient Swimming Strategies in a Three Dimensional Chaotic Flow by Reinforcement Learning—0
Costate-focused models for reinforcement learning—0
BBQ-Networks: Efficient Exploration in Deep Reinforcement Learning for Task-Oriented Dialogue Systems—0
Markov Decision Processes with Continuous Side Information—0
Variational Adaptive-Newton Method for Explorative Learning—0
Saliency-based Sequential Image Attention with Multiset Prediction—0
Reinforcement Learning in a large scale photonic Recurrent Neural Network—0
Classical Structured Prediction Losses for Sequence to Sequence Learning—0
Loss Functions for Multiset Prediction—0
Accelerated Method for Stochastic Composition Optimization with Nonsmooth Regularization—0
Applications of Deep Learning and Reinforcement Learning to Biological Data—0
Reinforcement Learning of Speech Recognition System Based on Policy Gradient and Hypothesis Selection—0
Towards the Use of Deep Reinforcement Learning with Global Policy For Query-based Extractive SummarisationCode0
Worm-level Control through Search-based Reinforcement Learning—0
An Empirical Analysis of Multiple-Turn Reasoning Strategies in Reading Comprehension Tasks—0
Energy Storage Arbitrage in Real-Time Markets via Reinforcement Learning—0
LatentPoison - Adversarial Attacks On The Latent SpaceCode0
Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games?Code0
Double Q(σ) and Q(σ, λ): Unifying Reinforcement Learning Control Algorithms—0
Composing Meta-Policies for Autonomous Driving Using Hierarchical Deep Reinforcement Learning—0
Policy Optimization by Genetic Distillation—0
A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning—0
Adaptive coordination of working-memory and reinforcement learning in non-human primates performing a trial-and-error problem solving taskCode0
Automatic Text Summarization Using Reinforcement Learning with Embedding Features—0
Intelligent Parameter Tuning in Optimization-based Iterative CT Reconstruction via Deep Reinforcement Learning—0
Learning to Diagnose: Assimilating Clinical Narratives using Deep Reinforcement Learning—0
Acquiring Target Stacking Skills by Goal-Parameterized Deep Reinforcement Learning—0
Paraphrase Generation with Deep Reinforcement Learning—0
Regret Minimization for Partially Observable Deep Reinforcement LearningCode0
TreeQN and ATreeC: Differentiable Tree-Structured Models for Deep Reinforcement LearningCode0
Visualizing and Understanding Atari AgentsCode0
Backpropagation through the Void: Optimizing control variates for black-box gradient estimationCode0
Automata-Guided Hierarchical Reinforcement Learning for Skill Composition—0
Artificial Intelligence as Structural Estimation: Economic Interpretations of Deep Blue, Bonanza, and AlphaGo—0
Exponential improvements for quantum-accessible reinforcement learning—0
Action-depedent Control Variates for Policy Optimization via Stein's IdentityCode0
Predicting Head Movement in Panoramic Video: A Deep Reinforcement Learning ApproachCode0
Unifying Value Iteration, Advantage Learning, and Dynamic Policy Programming—0
Sequence-to-Sequence ASR Optimization via Reinforcement Learning—0
Diff-DAC: Distributed Actor-Critic for Average Multitask Deep Reinforcement Learning—0
Inverse Reinforcement Learning Under Noisy Observations—0
Show:102550
← PrevPage 285 of 303Next →

Benchmark Results

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