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 5751–5800 of 15113 papers

TitleStatusHype
A Deep Reinforcement Learning Framework for Rapid Diagnosis of Whole Slide Pathological Images—0
General sum stochastic games with networked information flows—0
A Temporal-Pattern Backdoor Attack to Deep Reinforcement Learning—0
Multi-Agent Deep Reinforcement Learning in Vehicular OCC—0
Rapid Locomotion via Reinforcement Learning—0
Pessimism meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning—0
Multivariate Prediction Intervals for Random ForestsCode1
State Representation Learning for Goal-Conditioned Reinforcement Learning—0
Exploring the Benefits of Teams in Multiagent Learning—0
Using Deep Reinforcement Learning to solve Optimal Power Flow problem with generator failures—0
Multi-subgoal Robot Navigation in Crowds with History Information and Interactions—0
Meta-Cognition. An Inverse-Inverse Reinforcement Learning Approach for Cognitive Radars—0
RLFlow: Optimising Neural Network Subgraph Transformation with World ModelsCode0
Triangular Dropout: Variable Network Width without Retraining—0
Exploration in Deep Reinforcement Learning: A Survey—0
Large Neighborhood Search based on Neural Construction HeuristicsCode1
Deep-Attack over the Deep Reinforcement Learning—0
CCLF: A Contrastive-Curiosity-Driven Learning Framework for Sample-Efficient Reinforcement LearningCode1
Integrating Question Rewrites in Conversational Question Answering: A Reinforcement Learning Approach—0
Rewarding Semantic Similarity under Optimized Alignments for AMR-to-Text Generation—0
Reinforced Cross-modal Alignment for Radiology Report GenerationCode0
[CASPI] Causal-aware Safe Policy Improvement for Task-oriented Dialogue—0
Processing Network Controls via Deep Reinforcement Learning—0
Stable Reinforcement Learning for Optimal Frequency Control: A Distributed Averaging-Based Integral Approach—0
Data-driven control of spatiotemporal chaos with reduced-order neural ODE-based models and reinforcement learning—0
Learning user-defined sub-goals using memory editing in reinforcement learning—0
TTOpt: A Maximum Volume Quantized Tensor Train-based Optimization and its Application to Reinforcement LearningCode1
Markov Abstractions for PAC Reinforcement Learning in Non-Markov Decision ProcessesCode0
Unsupervised Reinforcement Learning for Transferable Manipulation Skill Discovery—0
Cost Effective MLaaS Federation: A Combinatorial Reinforcement Learning ApproachCode0
RISCLESS: A Reinforcement Learning Strategy to Exploit Unused Cloud Resources—0
Toward Compositional Generalization in Object-Oriented World Modeling—0
Actor-Critic Scheduling for Path-Aware Air-to-Ground Multipath Multimedia Delivery—0
Bisimulation Makes Analogies in Goal-Conditioned Reinforcement Learning—0
Accelerating Robot Learning of Contact-Rich Manipulations: A Curriculum Learning StudyCode1
Relational Abstractions for Generalized Reinforcement Learning on Symbolic Problems—0
RAMBO-RL: Robust Adversarial Model-Based Offline Reinforcement LearningCode1
Multi-Agent Reinforcement Learning for Traffic Signal Control through Universal Communication MethodCode1
Toward Policy Explanations for Multi-Agent Reinforcement LearningCode0
Social learning spontaneously emerges by searching optimal heuristics with deep reinforcement learningCode0
Learning Eco-Driving Strategies at Signalized Intersections—0
An Efficient Dynamic Sampling Policy For Monte Carlo Tree Search—0
BATS: Best Action Trajectory Stitching—0
Deep Reinforcement Learning for Orienteering Problems Based on Decomposition—0
Multi-objective Pointer Network for Combinatorial OptimizationCode0
Towards Evaluating Adaptivity of Model-Based Reinforcement Learning MethodsCode0
Skill-based Meta-Reinforcement Learning—0
Predicting Real-time Scientific Experiments Using Transformer models and Reinforcement LearningCode0
Task-Induced Representation Learning—0
Deep Reinforcement Learning for Online Routing of Unmanned Aerial Vehicles with Wireless Power Transfer—0
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Benchmark Results

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