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

Showing 69517000 of 15113 papers

TitleStatusHype
Applications of Reinforcement Learning in Deregulated Power Market: A Comprehensive Review0
Deep Reinforcement Learning-Based Adaptive IRS Control with Limited Feedback Codebooks0
Dynamically writing coupled memories using a reinforcement learning agent, meeting physical bounds0
How to Spend Your Robot Time: Bridging Kickstarting and Offline Reinforcement Learning for Vision-based Robotic Manipulation0
JUNO: Jump-Start Reinforcement Learning-based Node Selection for UWB Indoor Localization0
Goal-Oriented Next Best Activity Recommendation using Reinforcement Learning0
A Deep Reinforcement Learning-based Sliding Mode Control Design for Partially-known Nonlinear Systems0
Alternating Good-for-MDP Automata0
Reinforcement Learning Approach to Estimation in Linear Systems0
Rapid Locomotion via Reinforcement Learning0
Multi-Agent Deep Reinforcement Learning in Vehicular OCC0
Pessimism meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning0
General sum stochastic games with networked information flows0
LDSA: Learning Dynamic Subtask Assignment in Cooperative Multi-Agent Reinforcement Learning0
Generative methods for sampling transition paths in molecular dynamics0
A Deep Reinforcement Learning Framework for Rapid Diagnosis of Whole Slide Pathological Images0
A Temporal-Pattern Backdoor Attack to Deep Reinforcement Learning0
Exploring the Benefits of Teams in Multiagent Learning0
State Representation Learning for Goal-Conditioned Reinforcement Learning0
Multi-subgoal Robot Navigation in Crowds with History Information and Interactions0
Using Deep Reinforcement Learning to solve Optimal Power Flow problem with generator failures0
Meta-Cognition. An Inverse-Inverse Reinforcement Learning Approach for Cognitive Radars0
RLFlow: Optimising Neural Network Subgraph Transformation with World ModelsCode0
Triangular Dropout: Variable Network Width without Retraining0
Deep-Attack over the Deep Reinforcement Learning0
Exploration in Deep Reinforcement Learning: A Survey0
Integrating Question Rewrites in Conversational Question Answering: A Reinforcement Learning Approach0
Learning user-defined sub-goals using memory editing in reinforcement learning0
[CASPI] Causal-aware Safe Policy Improvement for Task-oriented Dialogue0
Data-driven control of spatiotemporal chaos with reduced-order neural ODE-based models and reinforcement learning0
Rewarding Semantic Similarity under Optimized Alignments for AMR-to-Text Generation0
Stable Reinforcement Learning for Optimal Frequency Control: A Distributed Averaging-Based Integral Approach0
Reinforced Cross-modal Alignment for Radiology Report GenerationCode0
Processing Network Controls via Deep Reinforcement Learning0
Markov Abstractions for PAC Reinforcement Learning in Non-Markov Decision ProcessesCode0
Unsupervised Reinforcement Learning for Transferable Manipulation Skill Discovery0
Cost Effective MLaaS Federation: A Combinatorial Reinforcement Learning ApproachCode0
Actor-Critic Scheduling for Path-Aware Air-to-Ground Multipath Multimedia Delivery0
Toward Compositional Generalization in Object-Oriented World Modeling0
RISCLESS: A Reinforcement Learning Strategy to Exploit Unused Cloud Resources0
Relational Abstractions for Generalized Reinforcement Learning on Symbolic Problems0
Bisimulation Makes Analogies in Goal-Conditioned Reinforcement Learning0
BATS: Best Action Trajectory Stitching0
Learning Eco-Driving Strategies at Signalized Intersections0
An Efficient Dynamic Sampling Policy For Monte Carlo Tree Search0
Social learning spontaneously emerges by searching optimal heuristics with deep reinforcement learningCode0
Toward Policy Explanations for Multi-Agent Reinforcement LearningCode0
Skill-based Meta-Reinforcement Learning0
Predicting Real-time Scientific Experiments Using Transformer models and Reinforcement LearningCode0
Task-Induced Representation Learning0
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Benchmark Results

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