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 5001–5050 of 15113 papers

TitleStatusHype
Self-Supervised Exploration via Temporal Inconsistency in Reinforcement Learning—0
Evolutionary Quantum Architecture Search for Parametrized Quantum Circuits—0
A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning—0
GenTUS: Simulating User Behaviour and Language in Task-oriented Dialogues with Generative Transformers—0
An intelligent algorithmic trading based on a risk-return reinforcement learning algorithm—0
Solving Royal Game of Ur Using Reinforcement LearningCode0
What deep reinforcement learning tells us about human motor learning and vice-versa—0
Some Supervision Required: Incorporating Oracle Policies in Reinforcement Learning via Epistemic Uncertainty Metrics—0
Quantum Multi-Agent Meta Reinforcement Learning—0
Improving Sample Efficiency in Evolutionary RL Using Off-Policy Ranking—0
BARReL: Bottleneck Attention for Adversarial Robustness in Vision-Based Reinforcement Learning—0
Incorporating Rivalry in Reinforcement Learning for a Competitive GameCode0
Weighted Maximum Entropy Inverse Reinforcement Learning—0
Spectral Decomposition Representation for Reinforcement Learning—0
Unified Policy Optimization for Continuous-action Reinforcement Learning in Non-stationary Tasks and Games—0
Entropy Augmented Reinforcement Learning—0
Improving Post-Processing of Audio Event Detectors Using Reinforcement LearningCode0
MARTI-4: new model of human brain, considering neocortex and basal ganglia -- learns to play Atari game by reinforcement learning on a single CPU—0
A Review of Uncertainty for Deep Reinforcement Learning—0
Hybrid Learning with New Value Function for the Maximum Common Subgraph Problem—0
Explainable Reinforcement Learning on Financial Stock Trading using SHAP—0
Intelligent problem-solving as integrated hierarchical reinforcement learning—0
Choquet regularization for reinforcement learning—0
Autonomous Resource Management in Construction Companies Using Deep Reinforcement Learning Based on IoT—0
Performance Optimization for Semantic Communications: An Attention-based Reinforcement Learning Approach—0
Sampling Through the Lens of Sequential Decision Making—0
Path Planning of Cleaning Robot with Reinforcement Learning—0
Metric Residual Networks for Sample Efficient Goal-Conditioned Reinforcement LearningCode1
Data-driven End-to-end Learning of Pole Placement Control for Nonlinear Dynamics via Koopman Invariant Subspaces—0
A Walk in the Park: Learning to Walk in 20 Minutes With Model-Free Reinforcement LearningCode2
A Deep Reinforcement Learning-based Adaptive Charging Policy for Wireless Rechargeable Sensor Networks—0
Hybrid UAV-enabled Secure Offloading via Deep Reinforcement Learning—0
Reinforcement Learning to Rank with Coarse-grained Labels—0
PD-MORL: Preference-Driven Multi-Objective Reinforcement Learning AlgorithmCode1
Making Reinforcement Learning Work on Swimmer—0
Reward Design For An Online Reinforcement Learning Algorithm Supporting Oral Self-CareCode0
Deep Reinforcement Learning for RIS-Assisted FD Systems: Single or Distributed RIS?—0
Transformer-based Value Function Decomposition for Cooperative Multi-agent Reinforcement Learning in StarCraftCode1
Online 3D Bin Packing Reinforcement Learning Solution with Buffer—0
Widely Used and Fast De Novo Drug Design by a Protein Sequence-Based Reinforcement Learning Model—0
Trustworthy Federated Learning via Blockchain—0
RLang: A Declarative Language for Describing Partial World Knowledge to Reinforcement Learning Agents—0
Low Emission Building Control with Zero-Shot Reinforcement Learning—0
Diffusion Policies as an Expressive Policy Class for Offline Reinforcement LearningCode2
Bayesian Soft Actor-Critic: A Directed Acyclic Strategy Graph Based Deep Reinforcement LearningCode1
Distributionally Robust Model-Based Offline Reinforcement Learning with Near-Optimal Sample Complexity—0
A Modular Framework for Reinforcement Learning Optimal ExecutionCode1
Multi-Agent Reinforcement Learning with Graph Convolutional Neural Networks for optimal Bidding Strategies of Generation Units in Electricity Markets—0
Towards Sequence-Level Training for Visual TrackingCode1
Mixed-Precision Neural Networks: A Survey—0
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Benchmark Results

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