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 14551–14600 of 15113 papers

TitleStatusHype
Particle Value Functions—0
Using Reinforcement Learning for Demand Response of Domestic Hot Water Buffers: a Real-Life Demonstration—0
Finite Sample Analysis of Two-Timescale Stochastic Approximation with Applications to Reinforcement Learning—0
A Hierarchical Framework of Cloud Resource Allocation and Power Management Using Deep Reinforcement Learning—0
Reinforcement Learning for Transition-Based Mention Detection—0
Sensor Fusion for Robot Control through Deep Reinforcement Learning—0
Micro-Objective Learning : Accelerating Deep Reinforcement Learning through the Discovery of Continuous Subgoals—0
Communications that Emerge through Reinforcement Learning Using a (Recurrent) Neural Network—0
What can you do with a rock? Affordance extraction via word embeddings—0
Sample Efficient Feature Selection for Factored MDPs—0
Tactics of Adversarial Attack on Deep Reinforcement Learning Agents—0
Tree-Structured Reinforcement Learning for Sequential Object Localization—0
Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning—0
Deep Variation-structured Reinforcement Learning for Visual Relationship and Attribute DetectionCode0
Functions that Emerge through End-to-End Reinforcement Learning - The Direction for Artificial General Intelligence -—0
Third-Person Imitation LearningCode0
Surprise-Based Intrinsic Motivation for Deep Reinforcement Learning—0
Neural Episodic ControlCode0
Unsupervised Basis Function Adaptation for Reinforcement Learning—0
Multi-step Reinforcement Learning: A Unifying Algorithm—0
FeUdal Networks for Hierarchical Reinforcement LearningCode0
Generalised Discount Functions applied to a Monte-Carlo AImu ImplementationCode0
Actor-Critic Reinforcement Learning with Simultaneous Human Control and Feedback—0
EX2: Exploration with Exemplar Models for Deep Reinforcement LearningCode0
Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction—0
A Laplacian Framework for Option Discovery in Reinforcement LearningCode0
Learning to Optimize Neural Nets—0
Reinforcement Learning for Pivoting TaskCode0
Show, Attend and Interact: Perceivable Human-Robot Social Interaction through Neural Attention Q-Network—0
Bridging the Gap Between Value and Policy Based Reinforcement Learning—0
Analysis of Agent Expertise in Ms. Pac-Man using Value-of-Information-based Policies—0
Analysing Congestion Problems in Multi-agent Reinforcement Learning—0
A Dataset for Developing and Benchmarking Active Vision—0
Neural Map: Structured Memory for Deep Reinforcement LearningCode0
Reinforcement Learning with Deep Energy-Based PoliciesCode0
Learning Control for Air Hockey Striking using Deep Reinforcement Learning—0
Stochastic Variance Reduction Methods for Policy Evaluation—0
Robot gains Social Intelligence through Multimodal Deep Reinforcement Learning—0
Online Meta-learning by Parallel Algorithm Competition—0
Control of Gene Regulatory Networks with Noisy Measurements and Uncertain Inputs—0
Changing Model Behavior at Test-Time Using Reinforcement Learning—0
Automatic Representation for Lifetime Value Recommender Systems—0
Data Distillation for Controlling Specificity in Dialogue Generation—0
Tackling Error Propagation through Reinforcement Learning: A Case of Greedy Dependency ParsingCode0
Real-time visual tracking by deep reinforced decision makingCode0
Towards a Common Implementation of Reinforcement Learning for Multiple Robotic TasksCode0
Reinforcement Learning Based Argument Component Detection—0
Beating the World's Best at Super Smash Bros. with Deep Reinforcement LearningCode0
Active One-shot LearningCode0
Learning to Repeat: Fine Grained Action Repetition for Deep Reinforcement Learning—0
Show:102550
← PrevPage 292 of 303Next →

Benchmark Results

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