Reinforcement Learning Approach

Reinforcement learning (RL) is a machine learning paradigm focused on training agents to make optimal decisions in dynamic environments by maximizing cumulative rewards. Current research emphasizes applying RL to diverse problems, including optimizing complex processes (e.g., space mission planning, manufacturing, traffic control), often employing algorithms like Proximal Policy Optimization (PPO) and Deep Q-Networks (DQN) with neural network architectures. This approach offers significant potential for improving efficiency and adaptability in various fields, from robotics and resource management to financial modeling and healthcare.

Papers

October 30, 2024

Adaptive Network Intervention for Complex Systems: A Hierarchical Graph Reinforcement Learning Approach
Qiliang Chen, Babak Heydari
Complex System Reinforcement Learning Approach Social Learning Adaptive Intervention Hierarchical Graph

October 17, 2024

Approximating Auction Equilibria with Reinforcement Learning
Pranjal Rawat
Reinforcement Learning Nash Equilibrium Reinforcement Learning Approach Optimal Bidding Strategy

October 15, 2024

Self-Supervised Learning For Robust Robotic Grasping In Dynamic Environment
Ankit Shaw
Self Supervised Learning Environment Feature Robotic Hand Robotic Task Service Robot Reinforcement Learning Approach Robust Grasping

September 25, 2024

Revisiting Space Mission Planning: A Reinforcement Learning-Guided Approach for Multi-Debris Rendezvous
Agni Bandyopadhyay, Guenther Waxenegger-Wilfing
Deep Reinforcement Learning Constructive Approach Proximal Policy Optimization Positive Reinforcement Reinforcement Learning Approach Rendezvous Problem Space Debris Mission Planning Space Debris Removal

September 5, 2024

Reinforcement Learning Approach to Optimizing Profilometric Sensor Trajectories for Surface Inspection
Sara Roos-Hoefgeest, Mario Roos-Hoefgeest, Ignacio Alvarez, Rafael C. González
Reinforcement Learning Approach Robot Trajectory Surface Defect Detection Shape Sensing Surface Inspection Inspection Path

August 18, 2024

Exploratory Optimal Stopping: A Singular Control Formulation
Jodi Dianetti, Giorgio Ferrari, Renyuan Xu
Reinforcement Learning Algorithm Reinforcement Learning Approach Optimal Stopping Problem

July 24, 2024

Path Following and Stabilisation of a Bicycle Model using a Reinforcement Learning Approach
Sebastian Weyrer, Peter Manzl, A. L. Schwab, Johannes Gerstmayr
Reinforcement Learning Reinforcement Learning Approach Multibody Dynamic Path Following Self Stabilization Effect Bicycle Model

July 8, 2024

System stabilization with policy optimization on unstable latent manifolds
Steffen W. R. Werner, Benjamin Peherstorfer
Reinforcement Learning Dynamical System Policy OpTimization Reinforcement Learning Approach Latent Manifold Low Dimensional Automatic Stabilization

June 26, 2024

Confident Natural Policy Gradient for Local Planning in $q_π$-realizable Constrained MDPs
Tian Tian, Lin F. Yang, Csaba Szepesvári
Policy Gradient Linear Function Approximation Reinforcement Learning Approach Constrained Markov Decision Process Local Planning

June 21, 2024

Towards General Negotiation Strategies with End-to-End Reinforcement Learning
Bram M. Renting, Thomas M. Moerland, Holger H. Hoos, Catholijn M. Jonker
Reinforcement Learning End to End Reinforcement Learning Approach Negotiation Strategy Agent Negotiation Never Before Seen Negotiation Problem

May 14, 2024

Hierarchical Resource Partitioning on Modern GPUs: A Reinforcement Learning Approach
Urvij Saroliya, Eishi Arima, Dai Liu, Martin Schulz
Reinforcement Learning Approach Multi GPU Computing Cluster Heterogeneous GPU

April 19, 2024

Reinforcement Learning Approach for Integrating Compressed Contexts into Knowledge Graphs
Ngoc Quach, Qi Wang, Zijun Gao, Qifeng Sun, Bo Guan, Lillian Floyd
Reinforcement Learning Knowledge Graph Reinforcement Learning Approach Context Compression

April 17, 2024

VC Theory for Inventory Policies
Yaqi Xie, Will Ma, Linwei Xin
Reinforcement Learning Approach Prospect Theory Sale Pattern Inventory Policy

March 18, 2024

Locomotion Generation for a Rat Robot based on Environmental Changes via Reinforcement Learning
Xinhui Shan, Yuhong Huang, Zhenshan Bing, Zitao Zhang, Xiangtong Yao, Kai Huang, Alois Knoll
Reinforcement Learning Reinforcement Learning Approach Robust Locomotion Dynamic Locomotion Robot Locomotion Robot Dog Environmental Change

February 24, 2024

Scalable Volt-VAR Optimization using RLlib-IMPALA Framework: A Reinforcement Learning Approach
Alaa Selim, Yanzhu Ye, Junbo Zhao, Bo Yang
Deep Reinforcement Learning Reinforcement Learning Approach Based Volt Var Control

February 17, 2024

Reinforcement learning to maximise wind turbine energy generation
Daniel Soler, Oscar Mariño, David Huergo, Martín de Frutos, Esteban Ferrer
Reinforcement Learning Reinforcement Learning Approach Wind Turbine Double Deep Q Learning

February 15, 2024

Reinforcement Learning for Solving Stochastic Vehicle Routing Problem with Time Windows
Zangir Iklassov, Ikboljon Sobirov, Ruben Solozabal, Martin Takac
Reinforcement Learning Reinforcement Learning Approach Time Window

December 29, 2023

Design Space Exploration of Approximate Computing Techniques with a Reinforcement Learning Approach
Sepide Saeedi, Alessandro Savino, Stefano Di Carlo
Reinforcement Learning Reinforcement Learning Approach Design Space Exploration Approximate Computing

October 29, 2023

Spacecraft Autonomous Decision-Planning for Collision Avoidance: a Reinforcement Learning Approach
Nicolas Bourriez, Adrien Loizeau, Adam F. Abdin
Collision Avoidance Observable Markov Decision Process Reinforcement Learning Approach Autonomous Spacecraft Space Domain Awareness Free Space Detection

October 8, 2023

Initial Task Assignment in Multi-Human Multi-Robot Teams: An Attention-enhanced Hierarchical Reinforcement Learning Approach
Ruiqi Wang, Dezhong Zhao, Arjun Gupte, Byung-Cheol Min
Reinforcement Learning Approach Human Robot Team Multi Robot Team Agent Team

Reinforcement Learning Approach

Papers

Adaptive Network Intervention for Complex Systems: A Hierarchical Graph Reinforcement Learning Approach

Approximating Auction Equilibria with Reinforcement Learning

Self-Supervised Learning For Robust Robotic Grasping In Dynamic Environment

Revisiting Space Mission Planning: A Reinforcement Learning-Guided Approach for Multi-Debris Rendezvous

Reinforcement Learning Approach to Optimizing Profilometric Sensor Trajectories for Surface Inspection

Exploratory Optimal Stopping: A Singular Control Formulation

Path Following and Stabilisation of a Bicycle Model using a Reinforcement Learning Approach

System stabilization with policy optimization on unstable latent manifolds

Confident Natural Policy Gradient for Local Planning in $q_π$-realizable Constrained MDPs

Towards General Negotiation Strategies with End-to-End Reinforcement Learning

Hierarchical Resource Partitioning on Modern GPUs: A Reinforcement Learning Approach

Reinforcement Learning Approach for Integrating Compressed Contexts into Knowledge Graphs

VC Theory for Inventory Policies

Locomotion Generation for a Rat Robot based on Environmental Changes via Reinforcement Learning

Scalable Volt-VAR Optimization using RLlib-IMPALA Framework: A Reinforcement Learning Approach

Reinforcement learning to maximise wind turbine energy generation

Reinforcement Learning for Solving Stochastic Vehicle Routing Problem with Time Windows

Design Space Exploration of Approximate Computing Techniques with a Reinforcement Learning Approach

Spacecraft Autonomous Decision-Planning for Collision Avoidance: a Reinforcement Learning Approach

Initial Task Assignment in Multi-Human Multi-Robot Teams: An Attention-enhanced Hierarchical Reinforcement Learning Approach