Reinforcement Learning Model

Reinforcement learning (RL) models aim to train agents to make optimal decisions in dynamic environments by learning from trial-and-error interactions. Current research focuses on improving reward function design, exploring alternative neural network architectures like Kolmogorov-Arnold Networks for more efficient learning, and developing methods to enhance training stability and sample efficiency, including offline RL and techniques leveraging large language models for data augmentation or imitation learning. These advancements are impacting diverse fields, from optimizing traffic flow and logistics to improving human-robot interaction and personalizing financial advice, by enabling the development of more effective and adaptable intelligent systems.

Papers

November 14, 2024

Rationality based Innate-Values-driven Reinforcement Learning
Qin Yang
Intrinsic Motivation Reinforcement Learning Model

November 13, 2024

Precision-Focused Reinforcement Learning Model for Robotic Object Pushing
Lara Bergmann, David Leins, Robert Haschke, Klaus Neumann
Non Humanoid Robot Robot Person Proprioceptive Sensing Non Prehensile Manipulation Reinforcement Learning Model

September 5, 2024

ELO-Rated Sequence Rewards: Advancing Reinforcement Learning Models
Qi Ju, Falin Hei, Zhemei Fang, Yunfeng Luo
Reinforcement Learning Deep Learning Reinforcement Learning Model Utility Based Learning Reward Reward Redistribution

August 9, 2024

Kolmogorov-Arnold Network for Online Reinforcement Learning
Victor Augusto Kich, Jair Augusto Bottega, Raul Steinmetz, Ricardo Bedin Grando, Ayano Yorozu, Akihisa Ohya
Proximal Policy Optimization Kolmogorov Arnold Network Online Reinforcement Learning Reinforcement Learning Model

May 22, 2024

ConcertoRL: An Innovative Time-Interleaved Reinforcement Learning Approach for Enhanced Control in Direct-Drive Tandem-Wing Vehicles
Minghao Zhang, Bifeng Song, Changhao Chen, Xinyu Lang
Reinforcement Learning Learning Based Vehicle Plan Reinforcement Learning Model Interleaving Method Enhanced Control Classical Control Insect Machine Hybrid System

February 22, 2024

Applying Reinforcement Learning to Optimize Traffic Light Cycles
Seungah Son, Juhee Jin
Reinforcement Learning Deep Q Network Traffic Flow Reinforcement Learning Model Traffic Light

February 13, 2024

LLM-driven Imitation of Subrational Behavior : Illusion or Reality?
Andrea Coletta, Kshama Dwarakanath, Penghang Liu, Svitlana Vyetrenko, Tucker Balch
Imitation Learning Real World Emergent Behavior Based Imitation Optical Illusion Reinforcement Learning Model

February 2, 2024

To the Max: Reinventing Reward in Reinforcement Learning
Grigorii Veviurko, Wendelin Böhmer, Mathijs de Weerdt
Reinforcement Learning Reward Function Reinforcement Learning Model

January 26, 2024

Reinforcement Learning Interventions on Boundedly Rational Human Agents in Frictionful Tasks
Eura Nofshin, Siddharth Swaroop, Weiwei Pan, Susan Murphy, Finale Doshi-Velez
Markov Decision Process AI Agent Artificial Intelligence Agent Reinforcement Learning Model Rational Agent Bounded Rational

January 17, 2024

Towards Off-Policy Reinforcement Learning for Ranking Policies with Human Feedback
Teng Xiao, Suhang Wang
Human Feedback Long Term Policy Reinforcement Learning User Behavior Expectation Maximization Reinforcement Learning Model Probabilistic Learning

January 12, 2024

Mutual Enhancement of Large Language and Reinforcement Learning Models through Bi-Directional Feedback Mechanisms: A Case Study
Shangding Gu
Reinforcement Learning Case Study Large Language Mutual Learning Teacher Student Feedback Mechanism Reinforcement Learning Model

September 7, 2023

Chat Failures and Troubles: Reasons and Solutions
Manal Helal, Patrick Holthaus, Gabriella Lakatos, Farshid Amirabdollahian
Artificial Intelligence Human Robot Interaction Solution Path Reason Giving Chat Model Reinforcement Learning Model Sex Trouble

July 22, 2023

Using Reinforcement Learning for the Three-Dimensional Loading Capacitated Vehicle Routing Problem
Stefan Schoepf, Stephen Mak, Julian Senoner, Liming Xu, Netland Torbjörn, Alexandra Brintrup
Reinforcement Learning Global Optimization Reinforcement Learning Model Capacitated Vehicle Routing Problem Collaborative Vehicle Routing

July 10, 2023

Loss Dynamics of Temporal Difference Reinforcement Learning
Blake Bordelon, Paul Masset, Henry Kuo, Cengiz Pehlevan
Reinforcement Learning Reward Shaping Temporal Difference Learning Temporal Difference Reinforcement Learning Model Gradient Descent Dynamic

June 10, 2023

HIPODE: Enhancing Offline Reinforcement Learning with High-Quality Synthetic Data from a Policy-Decoupled Approach
Shixi Lian, Yi Ma, Jinyi Liu, Yan Zheng, Zhaopeng Meng
Synthetic Data Offline Reinforcement Learning Reinforcement Learning Model Augmentation Policy Policy Decomposition

April 17, 2023

MDDL: A Framework for Reinforcement Learning-based Position Allocation in Multi-Channel Feed
Xiaowen Shi, Ze Wang, Yuanying Cai, Xiaoxu Wu, Fan Yang, Guogang Liao, Yongkang Wang, Xingxing Wang, Dong Wang
Reinforcement Learning New Framework Multi Channel Reinforcement Learning Model Multi Distribution

March 27, 2023

Model-Based Reinforcement Learning with Isolated Imaginations
Minting Pan, Xiangming Zhu, Yitao Zheng, Yunbo Wang, Xiaokang Yang
Autonomous Driving Model Based Reinforcement Learning Long Horizon Reinforcement Learning Model Transition Model Latent Imagination

March 10, 2023

Optimal foraging strategies can be learned
Gorka Muñoz-Gil, Andrea López-Incera, Lukas J. Fiderer, Hans J. Briegel
Reinforcement Learning Reinforcement Learning Model Level Based Foraging

February 24, 2023

GANterfactual-RL: Understanding Reinforcement Learning Agents' Strategies through Visual Counterfactual Explanations
Tobias Huber, Maximilian Demmler, Silvan Mertes, Matthew L. Olson, Elisabeth André
Reinforcement Learning Counterfactual Explanation Artificial Intelligence Model General Strategy Reinforcement Learning Agent Adversarial Method Reinforcement Learning Model Visual Counterfactual Explanation

November 19, 2022

LibSignal: An Open Library for Traffic Signal Control
Hao Mei, Xiaoliang Lei, Longchao Da, Bin Shi, Hua Wei
Traffic Signal Control State of the Art Reinforcement Reinforcement Learning Model Open Source Library Cross Simulator