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 6301–6350 of 15113 papers

TitleStatusHype
Intrinsic fluctuations of reinforcement learning promote cooperationCode0
MetaTrader: An Reinforcement Learning Approach Integrating Diverse Policies for Portfolio Optimization—0
Systems Theoretic Process Analysis of a Run Time Assured Neural Network Control System—0
Transmit Power Control for Indoor Small Cells: A Method Based on Federated Reinforcement Learning—0
A stabilizing reinforcement learning approach for sampled systems with partially unknown models—0
Deep Anomaly Detection and Search via Reinforcement Learning—0
Digital Twin Assisted Risk-Aware Sleep Mode Management Using Deep Q-Networks—0
Distributed Ensembles of Reinforcement Learning Agents for Electricity Control—0
An Analysis of Model-Based Reinforcement Learning From Abstracted Observations—0
Beyond Supervised Continual Learning: a Review—0
Evolutionary Deep Reinforcement Learning for Dynamic Slice Management in O-RAN—0
A further exploration of deep Multi-Agent Reinforcement Learning with Hybrid Action Space—0
Model-Based Reinforcement Learning with SINDy—0
Understanding the Limits of Poisoning Attacks in Episodic Reinforcement Learning—0
Reinforcement Learning for Hardware Security: Opportunities, Developments, and Challenges—0
Categorical semantics of compositional reinforcement learning—0
Goal-Conditioned Q-Learning as Knowledge DistillationCode0
Normality-Guided Distributional Reinforcement Learning for Continuous Control—0
Unsupervised Representation Learning in Deep Reinforcement Learning: A ReviewCode0
RL-DistPrivacy: Privacy-Aware Distributed Deep Inference for low latency IoT systems—0
SupervisorBot: NLP-Annotated Real-Time Recommendations of Psychotherapy Treatment Strategies with Deep Reinforcement Learning—0
Reinforcement Learning based Multi-connectivity Resource Allocation in Factory Automation Systems—0
Socially Fair Reinforcement Learning—0
Visual processing in context of reinforcement learning—0
Play with Emotion: Affect-Driven Reinforcement Learning—0
Symbolic Explanation of Affinity-Based Reinforcement Learning Agents with Markov Models—0
CH-MARL: A Multimodal Benchmark for Cooperative, Heterogeneous Multi-Agent Reinforcement Learning—0
DETERRENT: Detecting Trojans using Reinforcement Learning—0
An approach to implement Reinforcement Learning for Heterogeneous Vehicular Networks—0
Exploiting Deep Reinforcement Learning for Edge Caching in Cell-Free Massive MIMO Systems—0
ATTRITION: Attacking Static Hardware Trojan Detection Techniques Using Reinforcement Learning—0
Autonomous Unmanned Aerial Vehicle Navigation using Reinforcement Learning: A Systematic Review—0
A Comparison of Reinforcement Learning Frameworks for Software Testing TasksCode0
Importance Prioritized Policy DistillationCode0
Learning Task Automata for Reinforcement Learning using Hidden Markov Models—0
UAS Navigation in the Real World Using Visual Observation—0
Turning Mathematics Problems into Games: Reinforcement Learning and Gröbner bases together solve Integer Feasibility Problems—0
Variance Reduction based Experience Replay for Policy OptimizationCode0
Oracle-free Reinforcement Learning in Mean-Field Games along a Single Sample Path—0
Self-Supervised Exploration via Temporal Inconsistency in Reinforcement Learning—0
A model-based approach to meta-Reinforcement Learning: Transformers and tree search—0
Hierarchical Reinforcement Learning Based Video Semantic Coding for Segmentation—0
Dynamic Memory-based Curiosity: A Bootstrap Approach for Exploration—0
A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning—0
An intelligent algorithmic trading based on a risk-return reinforcement learning algorithm—0
Evolutionary Quantum Architecture Search for Parametrized Quantum Circuits—0
GenTUS: Simulating User Behaviour and Language in Task-oriented Dialogues with Generative Transformers—0
What deep reinforcement learning tells us about human motor learning and vice-versa—0
Solving Royal Game of Ur Using Reinforcement LearningCode0
Quantum Multi-Agent Meta Reinforcement Learning—0
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Benchmark Results

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