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 12201–12250 of 15113 papers

TitleStatusHype
Learning Action-Transferable Policy with Action EmbeddingCode0
Spatiotemporally Constrained Action Space Attacks on Deep Reinforcement Learning AgentsCode0
Rewarding Coreference Resolvers for Being Consistent with World KnowledgeCode0
Q-DATA: Enhanced Traffic Flow Monitoring in Software-Defined Networks applying Q-learning—0
Quasi-Newton Optimization Methods For Deep Learning Applications—0
No Press Diplomacy: Modeling Multi-Agent GameplayCode0
Learning sparse representations in reinforcement learning—0
Learning Dynamic Context Augmentation for Global Entity LinkingCode0
Inductive-bias-driven Reinforcement Learning For Efficient Schedules in Heterogeneous Clusters—0
Answers Unite! Unsupervised Metrics for Reinforced Summarization ModelsCode0
ACES -- Automatic Configuration of Energy Harvesting Sensors with Reinforcement Learning—0
LeDeepChef: Deep Reinforcement Learning Agent for Families of Text-Based Games—0
Augmented Memory Networks for Streaming-Based Active One-Shot Learning—0
A Reinforcement Learning-Based Framework for Solving Physical Design Routing Problem in the Absence of Large Test Sets—0
Generalization in Transfer Learning—0
How to Build User Simulators to Train RL-based Dialog SystemsCode0
Better Rewards Yield Better Summaries: Learning to Summarise Without ReferencesCode0
Evolutionary reinforcement learning of dynamical large deviations—0
Classification Betters Regression in Query-based Multi-document Summarisation Techniques for Question Answering: Macquarie University at BioASQ7b—0
Logic and the 2-Simplicial Transformer—0
Reinforcement Learning-based Automatic Diagnosis of Acute Appendicitis in Abdominal CT—0
To Combine or Not To Combine? A Rainbow Deep Reinforcement Learning Agent for Dialog Policies—0
Scalable Reinforcement-Learning-Based Neural Architecture Search for Cancer Deep Learning Research—0
Deep Reinforcement Learning with Distributional Semantic Rewards for Abstractive Summarization—0
Generating Classical Chinese Poems from Vernacular ChineseCode0
Reinforcement learning with world model—0
Learning to Transfer Learn: Reinforcement Learning-Based Selection for Adaptive Transfer Learning—0
PaccMann^RL: Designing anticancer drugs from transcriptomic data via reinforcement learning—0
Reinforcement Learning: Prediction, Control and Value Function Approximation—0
Solving Math Word Problems with Double-Decoder Transformer—0
An Empirical Comparison on Imitation Learning and Reinforcement Learning for Paraphrase GenerationCode0
Guided Dialog Policy Learning: Reward Estimation for Multi-Domain Task-Oriented DialogCode0
Deep Actor-Critic Reinforcement Learning for Anomaly Detection—0
Ensemble-Based Deep Reinforcement Learning for Chatbots—0
Continuous Value Iteration (CVI) Reinforcement Learning and Imaginary Experience Replay (IER) for learning multi-goal, continuous action and state space controllersCode0
Deep Reinforcement Learning for Chatbots Using Clustered Actions and Human-Likeness Rewards—0
A Deep Reinforcement Learning Approach to Multi-component Job Scheduling in Edge Computing—0
Dynamics-aware EmbeddingsCode0
Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning—0
Universal Policies to Learn Them AllCode0
A Comparison of Action Spaces for Learning Manipulation Tasks—0
Double Reinforcement Learning for Efficient Off-Policy Evaluation in Markov Decision ProcessesCode0
Improving the dynamics of quantum sensors with reinforcement learning—0
Reinforcement Learning in Healthcare: A Survey—0
Opponent Aware Reinforcement LearningCode0
Practical Risk Measures in Reinforcement Learning—0
On Convergence Rate of Adaptive Multiscale Value Function Approximation For Reinforcement Learning—0
Dialog State Tracking with Reinforced Data Augmentation—0
Deep Reinforcement Learning for Foreign Exchange Trading—0
A Generalized Algorithm for Multi-Objective Reinforcement Learning and Policy AdaptationCode0
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Benchmark Results

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