Reinforcement Learning Agent

Reinforcement learning (RL) agents are computational systems designed to learn optimal decision-making strategies through trial and error, aiming to maximize cumulative rewards within a defined environment. Current research emphasizes improving RL agent efficiency and robustness, focusing on areas like scalable architecture search, offline training with real-world and simulated data, and incorporating safety mechanisms and ethical considerations into agent design. These advancements are significant for diverse applications, including building energy optimization, personalized recommendations, and autonomous systems, driving progress in both theoretical understanding and practical deployment of RL.

Papers

December 14, 2023

Personalized Path Recourse for Reinforcement Learning Agents
Dat Hong, Tong Wang
Reinforcement Learning Reinforcement Learning Agent Algorithmic Recourse

December 7, 2023

CODEX: A Cluster-Based Method for Explainable Reinforcement Learning
Timothy K. Mathes, Jessica Inman, Andrés Colón, Simon Khan
Reinforcement Learning Counterfactual Explanation Reinforcement Learning Agent Agent Behavior State Action Space Explainable Reinforcement Learning Clustering Based Approach Game Representation

December 5, 2023

LExCI: A Framework for Reinforcement Learning with Embedded Systems
Kevin Badalian, Lucas Koch, Tobias Brinkmann, Mario Picerno, Marius Wegener, Sung-Yong Lee, Jakob Andert
Reinforcement Learning Artificial Intelligence New Framework Reinforcement Learning Agent Embedded System Reinforcement Learning Library

December 4, 2023

November 22, 2023

Large Language Model as a Policy Teacher for Training Reinforcement Learning Agents
Zihao Zhou, Bin Hu, Chenyang Zhao, Pu Zhang, Bin Liu
Large Language Model Reinforcement Learning Agent LLM Based Agent Based Policy

November 8, 2023

Fuzzy Ensembles of Reinforcement Learning Policies for Robotic Systems with Varied Parameters
Abdel Gafoor Haddad, Mohammed B. Mohiuddin, Igor Boiko, Yahya Zweiri
Reinforcement Learning Robotic System Many Parameter Reinforcement Learning Agent Parallel Training Classical Control Ensemble Aggregation

October 25, 2023

Transfer of Reinforcement Learning-Based Controllers from Model- to Hardware-in-the-Loop
Mario Picerno, Lucas Koch, Kevin Badalian, Marius Wegener, Joschka Schaub, Charles Robert Koch, Jakob Andert
Reinforcement Learning Full Model Formality Transfer Reinforcement Learning Agent Positive Reinforcement M$ Base Controller Hardware in the Loop Pre Trained Reinforcement Learning

October 14, 2023

LgTS: Dynamic Task Sampling using LLM-generated sub-goals for Reinforcement Learning Agents
Yash Shukla, Wenchang Gao, Vasanth Sarathy, Alvaro Velasquez, Robert Wright, Jivko Sinapov
Reinforcement Learning Task Planning Reinforcement Learning Agent Fine Tuned Large Language Model Semi Supervised Teacher Student Task Sampling

October 13, 2023

Automatic Music Playlist Generation via Simulation-based Reinforcement Learning
Federico Tomasi, Joseph Cauteruccio, Surya Kanoria, Kamil Ciosek, Matteo Rinaldi, Zhenwen Dai
Reinforcement Learning Reinforcement Learning Agent User Satisfaction Playlist Generation

September 27, 2023

DTC: Deep Tracking Control
Fabian Jenelten, Junzhe He, Farbod Farshidian, Marco Hutter
Trajectory Optimization Reinforcement Learning Agent Legged Locomotion Deep Reinforcement Learning Based Legged System

September 21, 2023

Representation Abstractions as Incentives for Reinforcement Learning Agents: A Robotic Grasping Case Study
Panagiotis Petropoulakis, Ludwig Gräf, Josip Josifovski, Mohammadhossein Malmir, Alois Knoll
Reinforcement Learning Agent Robotic Grasping Robot Control Robotic Task State Representation Task Specific Knowledge Institutional Incentive

September 13, 2023

Enhancing the Performance of Multi-Agent Reinforcement Learning for Controlling HVAC Systems
Daniel Bayer, Marco Pruckner
Reinforcement Learning Multi Agent Reinforcement Learning System Performance Reinforcement Learning Agent Heating, Ventilation, and Air Conditioning

September 1, 2023

End-to-end Lidar-Driven Reinforcement Learning for Autonomous Racing
Meraj Mammadov
Reinforcement Learning Reinforcement Learning Algorithm Reinforcement Learning Agent Autonomous Racing Racing Scenario

August 29, 2023

Adversarial Style Transfer for Robust Policy Optimization in Deep Reinforcement Learning
Md Masudur Rahman, Yexiang Xue
Reinforcement Learning Deep Reinforcement Learning Reinforcement Learning Agent Robust Policy Adversarial Reinforcement Learning Deep Reinforcement Learning Algorithm Adversarial Transfer

August 16, 2023

AI planning in the imagination: High-level planning on learned abstract search spaces
Carlos Martin, Tuomas Sandholm
Artificial Intelligence Task Planning Action Space Reinforcement Learning Agent Search Space Planning Algorithm Temporal Action

July 28, 2023

Dialogue Shaping: Empowering Agents through NPC Interaction
Wei Zhou, Xiangyu Peng, Mark Riedl
Reinforcement Learning Knowledge Graph Agent Smith Reinforcement Learning Agent Dialogue Task Text Based Game Environment Social NPC

July 26, 2023

Reinforcement Learning by Guided Safe Exploration
Qisong Yang, Thiago D. Simão, Nils Jansen, Simon H. Tindemans, Matthijs T. J. Spaan
Reinforcement Learning Reinforcement Learning Agent Reward Free Reward Free Reinforcement Learning

July 21, 2023

Hindsight-DICE: Stable Credit Assignment for Deep Reinforcement Learning
Akash Velu, Skanda Vaidyanath, Dilip Arumugam
Reinforcement Learning Deep Reinforcement Learning Policy Evaluation Reinforcement Learning Agent Hindsight Instruction

July 3, 2023

Achieving Stable Training of Reinforcement Learning Agents in Bimodal Environments through Batch Learning
E. Hurwitz, N. Peace, G. Cevora
Reinforcement Learning Reinforcement Learning Agent Stochastic Environment Reinforcement Learning Problem Stable Training Batch Learning Multimodal Environment Tabular Q Learning

Reinforcement Learning Agent

Papers

Personalized Path Recourse for Reinforcement Learning Agents

CODEX: A Cluster-Based Method for Explainable Reinforcement Learning

LExCI: A Framework for Reinforcement Learning with Embedded Systems

Training Reinforcement Learning Agents and Humans With Difficulty-Conditioned Generators

I-PHYRE: Interactive Physical Reasoning

Large Language Model as a Policy Teacher for Training Reinforcement Learning Agents

Fuzzy Ensembles of Reinforcement Learning Policies for Robotic Systems with Varied Parameters

Transfer of Reinforcement Learning-Based Controllers from Model- to Hardware-in-the-Loop

LgTS: Dynamic Task Sampling using LLM-generated sub-goals for Reinforcement Learning Agents

Automatic Music Playlist Generation via Simulation-based Reinforcement Learning

DTC: Deep Tracking Control

Representation Abstractions as Incentives for Reinforcement Learning Agents: A Robotic Grasping Case Study

Enhancing the Performance of Multi-Agent Reinforcement Learning for Controlling HVAC Systems

End-to-end Lidar-Driven Reinforcement Learning for Autonomous Racing

Adversarial Style Transfer for Robust Policy Optimization in Deep Reinforcement Learning

AI planning in the imagination: High-level planning on learned abstract search spaces

Dialogue Shaping: Empowering Agents through NPC Interaction

Reinforcement Learning by Guided Safe Exploration

Hindsight-DICE: Stable Credit Assignment for Deep Reinforcement Learning

Achieving Stable Training of Reinforcement Learning Agents in Bimodal Environments through Batch Learning