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

July 31, 2024

Formal Ethical Obligations in Reinforcement Learning Agents: Verification and Policy Updates
Colin Shea-Blymyer, Houssam Abbas
Complex Reasoning Verification Task Reinforcement Learning Agent Uncertain Environment Ethical Consideration Deontic Logic Policy Update

July 17, 2024

Estimating Reaction Barriers with Deep Reinforcement Learning
Adittya Pal
Deep Reinforcement Learning High Dimensional Reinforcement Learning Agent Knowledge Barrier

July 6, 2024

A Novel Bifurcation Method for Observation Perturbation Attacks on Reinforcement Learning Agents: Load Altering Attacks on a Cyber Physical Power System
Kiernan Broda-Milian, Ranwa Al-Mallah, Hanane Dagdougui
Adversarial Attack Deep Reinforcement Learning Adversarial Example New Attack Reinforcement Learning Agent Renewable Energy Cyber Physical Bifurcation Diagram Untargeted Attack Norm Attack

June 26, 2024

Mental Modeling of Reinforcement Learning Agents by Language Models
Wenhao Lu, Xufeng Zhao, Josua Spisak, Jae Hee Lee, Stefan Wermter
Language Model Reinforcement Learning Agent Mental Model

June 6, 2024

Behavior-Targeted Attack on Reinforcement Learning with Limited Access to Victim's Policy
Shojiro Yamabe, Kazuto Fukuchi, Ryoma Senda, Jun Sakuma
Reinforcement Learning Reinforcement Learning Agent Health Policy Recommendation Reinforcement Learning Benchmark Attack Method Adversarial Change Male Victim

May 30, 2024

SleeperNets: Universal Backdoor Poisoning Attacks Against Reinforcement Learning Agents
Ethan Rathbun, Christopher Amato, Alina Oprea
Reinforcement Learning Adversarial Attack Reinforcement Learning Agent Backdoor Poisoning Attack Training Time Attack Universal Backdoor

May 28, 2024

PyTAG: Tabletop Games for Multi-Agent Reinforcement Learning
Martin Balla, George E. M. Long, James Goodman, Raluca D. Gaina, Diego Perez-Liebana
Multi Agent Reinforcement Learning Proximal Policy Optimization Reinforcement Learning Agent Multi Agent Setting Game Playing Agent Tabletop Game

May 23, 2024

Which Experiences Are Influential for RL Agents? Efficiently Estimating The Influence of Experiences
Takuya Hiraoka, Guanquan Wang, Takashi Onishi, Yoshimasa Tsuruoka
Reinforcement Learning External Influence Reinforcement Learning Agent Structured Dropout Experience Replay eXperience Report Policy Iteration

May 16, 2024

Simulation-Based Benchmarking of Reinforcement Learning Agents for Personalized Retail Promotions
Yu Xia, Sriram Narayanamoorthy, Zhengyuan Zhou, Joshua Mabry
Reinforcement Learning Contextual Bandit Sparse Reward Reinforcement Learning Agent Simulation Benchmark

May 14, 2024

Python-Based Reinforcement Learning on Simulink Models
Georg Schäfer, Max Schirl, Jakob Rehrl, Stefan Huber, Simon Hirlaender
Reinforcement Learning Agent Reinforcement Learning Research Training Agent Simulink Simulator

May 7, 2024

In-context Learning for Automated Driving Scenarios
Ziqi Zhou, Jingyue Zhang, Jingyuan Zhang, Boyue Wang, Tianyu Shi, Alaa Khamis
Context Learning Automated Driving Reinforcement Learning Agent Semi Supervised Reward Current Reinforcement Learning

March 26, 2024

March 20, 2024

Reinforcement Learning for Online Testing of Autonomous Driving Systems: a Replication and Extension Study
Luca Giamattei, Matteo Biagiola, Roberto Pietrantuono, Stefano Russo, Paolo Tonella
Reinforcement Learning Autonomous Driving Autonomous Vehicle Q Learning Reinforcement Learning Algorithm Reinforcement Learning Agent Extension Study Serial Reproduction Online Exam

March 12, 2024

Do Agents Dream of Electric Sheep?: Improving Generalization in Reinforcement Learning through Generative Learning
Giorgio Franceschelli, Mirco Musolesi
Reinforcement Learning Strong Generalization Reinforcement Learning Agent Model Overfitting Generative Learning Electric SHEEP Agent DREAM Generative Blending Augmentation

March 6, 2024

Belief-Enriched Pessimistic Q-Learning against Adversarial State Perturbations
Xiaolin Sun, Zizhan Zheng
Reinforcement Learning Q Learning Reinforcement Learning Agent Robust Reinforcement Learning Belief State Diffusion Purification

March 5, 2024

Language Guided Exploration for RL Agents in Text Environments
Hitesh Golchha, Sahil Yerawar, Dhruvesh Patel, Soham Dan, Keerthiram Murugesan
Reinforcement Learning Agent Language Navigation Sequential Decision Making Decision Support Tabular Reinforcement Learning Text Based Environment

February 21, 2024

Enhancing Reinforcement Learning Agents with Local Guides
Paul Daoudi, Bogdan Robu, Christophe Prieur, Ludovic Dos Santos, Merwan Barlier
Reinforcement Learning Reinforcement Learning Agent Approximate Policy Iteration

February 6, 2024

Logical Specifications-guided Dynamic Task Sampling for Reinforcement Learning Agents
Yash Shukla, Tanushree Burman, Abhishek Kulkarni, Robert Wright, Alvaro Velasquez, Jivko Sinapov
Reinforcement Learning Temporal Logic Reinforcement Learning Agent Compositional Reinforcement Learning Task Sampling Observable Robotic

February 2, 2024

Brain-Like Replay Naturally Emerges in Reinforcement Learning Agents
Jiyi Wang, Likai Tang, Huimiao Chen, Marcelo G Mattar, Sen Song
Reinforcement Learning Reinforcement Learning Agent Episodic Memory Activation Pattern Nonlocal Model Cognitive Replay

Reinforcement Learning Agent

Papers

Formal Ethical Obligations in Reinforcement Learning Agents: Verification and Policy Updates

Estimating Reaction Barriers with Deep Reinforcement Learning

A Novel Bifurcation Method for Observation Perturbation Attacks on Reinforcement Learning Agents: Load Altering Attacks on a Cyber Physical Power System

Mental Modeling of Reinforcement Learning Agents by Language Models

Behavior-Targeted Attack on Reinforcement Learning with Limited Access to Victim's Policy

SleeperNets: Universal Backdoor Poisoning Attacks Against Reinforcement Learning Agents

PyTAG: Tabletop Games for Multi-Agent Reinforcement Learning

Which Experiences Are Influential for RL Agents? Efficiently Estimating The Influence of Experiences

Simulation-Based Benchmarking of Reinforcement Learning Agents for Personalized Retail Promotions

Python-Based Reinforcement Learning on Simulink Models

In-context Learning for Automated Driving Scenarios

Depending on yourself when you should: Mentoring LLM with RL agents to become the master in cybersecurity games

Towards a Zero-Data, Controllable, Adaptive Dialog System

Reinforcement Learning for Online Testing of Autonomous Driving Systems: a Replication and Extension Study

Do Agents Dream of Electric Sheep?: Improving Generalization in Reinforcement Learning through Generative Learning

Belief-Enriched Pessimistic Q-Learning against Adversarial State Perturbations

Language Guided Exploration for RL Agents in Text Environments

Enhancing Reinforcement Learning Agents with Local Guides

Logical Specifications-guided Dynamic Task Sampling for Reinforcement Learning Agents

Brain-Like Replay Naturally Emerges in Reinforcement Learning Agents