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 13551–13600 of 15113 papers

TitleStatusHype
Natural Language Person Search Using Deep Reinforcement Learning—0
Part-Activated Deep Reinforcement Learning for Action Prediction—0
Snap Angle Prediction for 360° Panoramas—0
Goal-Oriented Visual Question Generation via Intermediate Rewards—0
Collaborative Deep Reinforcement Learning for Multi-Object Tracking—0
Deep Reinforcement Learning with Iterative Shift for Visual Tracking—0
Dual-Agent Deep Reinforcement Learning for Deformable Face Tracking—0
A Contextual-bandit-based Approach for Informed Decision-making in Clinical Trials—0
Directed Exploration in PAC Model-Free Reinforcement Learning—0
Ensemble Sequence Level Training for Multimodal MT: OSU-Baidu WMT18 Multimodal Machine Translation System Report—0
APES: a Python toolbox for simulating reinforcement learning environmentsCode0
ExIt-OOS: Towards Learning from Planning in Imperfect Information GamesCode0
Application of Self-Play Reinforcement Learning to a Four-Player Game of Imperfect InformationCode0
A Reinforcement Learning-driven Translation Model for Search-Oriented Conversational Systems—0
Learning a Policy for Opportunistic Active Learning—0
APRIL: Interactively Learning to Summarise by Combining Active Preference Learning and Reinforcement LearningCode0
Cycle-of-Learning for Autonomous Systems from Human InteractionCode0
High-confidence error estimates for learned value functions—0
SOLAR: Deep Structured Representations for Model-Based Reinforcement LearningCode0
Optimal control of eye-movements during visual search—0
A Study of Reinforcement Learning for Neural Machine TranslationCode0
NavigationNet: A Large-scale Interactive Indoor Navigation Dataset—0
Proximal Policy Optimization and its Dynamic Version for Sequence Generation—0
Playing 20 Question Game with Policy-Based Reinforcement Learning—0
Exploring Shared Structures and Hierarchies for Multiple NLP Tasks—0
LIFT: Reinforcement Learning in Computer Systems by Learning From DemonstrationsCode0
Interactive Semantic Parsing for If-Then Recipes via Hierarchical Reinforcement LearningCode0
Catastrophic Importance of Catastrophic Forgetting—0
Goal-oriented Dialogue Policy Learning from Failures—0
Source-Critical Reinforcement Learning for Transferring Spoken Language Understanding to a New Language—0
Reinforcement Learning for Autonomous Defence in Software-Defined Networking—0
Importance mixing: Improving sample reuse in evolutionary policy search methods—0
Data Poisoning Attacks in Contextual Bandits—0
Context-Aware Visual Policy Network for Sequence-Level Image CaptioningCode0
Deep RTS: A Game Environment for Deep Reinforcement Learning in Real-Time Strategy GamesCode0
Incorporating Consistency Verification into Neural Data-to-Document Generation—0
Directed Policy Gradient for Safe Reinforcement Learning with Human Advice—0
A Framework for Automated Cellular Network Tuning with Reinforcement LearningCode0
Visual Sensor Network Reconfiguration with Deep Reinforcement Learning—0
End-to-end Active Object Tracking and Its Real-world Deployment via Reinforcement Learning—0
Policy Optimization as Wasserstein Gradient Flows—0
Regret Bounds for Reinforcement Learning via Markov Chain Concentration—0
An Efficient Deep Reinforcement Learning Model for Urban Traffic ControlCode0
Learning to Share and Hide Intentions using Information RegularizationCode0
RecoGym: A Reinforcement Learning Environment for the problem of Product Recommendation in Online AdvertisingCode0
Structured Dialogue Policy with Graph Neural Networks—0
Source Critical Reinforcement Learning for Transferring Spoken Language Understanding to a New Language—0
Multi-Agent Deep Reinforcement Learning for Dynamic Power Allocation in Wireless NetworksCode0
Neural Math Word Problem Solver with Reinforcement Learning—0
A Reinforcement Learning Framework for Natural Question Generation using Bi-discriminators—0
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Benchmark Results

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