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

June 19, 2023

Benchmarking Robustness of Deep Reinforcement Learning approaches to Online Portfolio Management
Marc Velay, Bich-Liên Doan, Arpad Rimmel, Fabrice Popineau, Fabrice Daniel
Deep Reinforcement Learning Reinforcement Learning Agent Robustness Benchmark DRL Algorithm Online Portfolio Selection

June 15, 2023

Semantic HELM: A Human-Readable Memory for Reinforcement Learning
Fabian Paischer, Thomas Adler, Markus Hofmarcher, Sepp Hochreiter
Reinforcement Learning Reinforcement Learning Agent Memory Mechanism Memory Formation

June 9, 2023

Large Language Models Are Semi-Parametric Reinforcement Learning Agents
Danyang Zhang, Lu Chen, Situo Zhang, Hongshen Xu, Zihan Zhao, Kai Yu
Reinforcement Learning Reinforcement Learning Agent Episodic Memory Human Memory

June 7, 2023

Generalization Across Observation Shifts in Reinforcement Learning
Anuj Mahajan, Amy Zhang
Reinforcement Learning Reinforcement Learning Agent Bisimulation Metric Covariate Shift Generalization

June 5, 2023

Risk-Aware Reward Shaping of Reinforcement Learning Agents for Autonomous Driving
Lin-Chi Wu, Zengjie Zhang, Sofie Haesaert, Zhiqiang Ma, Zhiyong Sun
Reinforcement Learning Autonomous Driving Reinforcement Learning Agent

June 4, 2023

Bad Habits: Policy Confounding and Out-of-Trajectory Generalization in RL
Miguel Suau, Matthijs T. J. Spaan, Frans A. Oliehoek
Reinforcement Learning Agent Handwritten Trajectory Human Like RL Confounding Bias Habitual Behavior State Action Trajectory Generalization

May 27, 2023

Online Nonstochastic Model-Free Reinforcement Learning
Udaya Ghai, Arushi Gupta, Wenhan Xia, Karan Singh, Elad Hazan
Reinforcement Learning Agent Linear Bandit Model Free Reinforcement Learning Regret Guarantee Linear Policy

April 30, 2023

A Transfer Learning Approach to Minimize Reinforcement Learning Risks in Energy Optimization for Smart Buildings
Mikhail Genkin, J. J. McArthur
Deep Reinforcement Learning Reinforcement Learning Agent Energy Efficiency Transfer Learning Approach Smart Building Risk Aware Reinforcement Learning

April 25, 2023

Proximal Curriculum for Reinforcement Learning Agents
Georgios Tzannetos, Bárbara Gomes Ribeiro, Parameswaran Kamalaruban, Adish Singla
Reinforcement Learning Reinforcement Learning Agent Proximal Curriculum Deep Reinforcement Learning Agent Curriculum Design

April 11, 2023

Automaton-Guided Curriculum Generation for Reinforcement Learning Agents
Yash Shukla, Abhishek Kulkarni, Robert Wright, Alvaro Velasquez, Jivko Sinapov
Reinforcement Learning Curriculum Learning Reinforcement Learning Agent Sequential Decision Making Problem Curriculum Generation

April 2, 2023

Experimentation Platforms Meet Reinforcement Learning: Bayesian Sequential Decision-Making for Continuous Monitoring
Runzhe Wan, Yu Liu, James McQueen, Doug Hains, Rui Song
Reinforcement Learning Reinforcement Learning Agent Hypothesis Testing Meta Analysis Optimal Decision Rule

March 2, 2023

Domain Adaptation of Reinforcement Learning Agents based on Network Service Proximity
Kaushik Dey, Satheesh K. Perepu, Pallab Dasgupta, Abir Das
Reinforcement Learning Domain Adaptation Reinforcement Learning Agent Proximity Search Communication Network

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

February 13, 2023

Universal Agent Mixtures and the Geometry of Intelligence
Samuel Allen Alexander, David Quarel, Len Du, Marcus Hutter
Multi Agent Reinforcement Learning Geometric Analysis Reinforcement Learning Agent Cognitive Intelligence

January 30, 2023

Transferring Multiple Policies to Hotstart Reinforcement Learning in an Air Compressor Management Problem
Hélène Plisnier, Denis Steckelmacher, Jeroen Willems, Bruno Depraetere, Ann Nowé
Reinforcement Learning Reinforcement Learning Agent Reward Shaping Diverse Policy Industrial Machine Policy Alignment Compressor Based Machine

January 28, 2023

Do Embodied Agents Dream of Pixelated Sheep: Embodied Decision Making using Language Guided World Modelling
Kolby Nottingham, Prithviraj Ammanabrolu, Alane Suhr, Yejin Choi, Hannaneh Hajishirzi, Sameer Singh, Roy Fox
Reinforcement Learning Decision Making Environment Exploration World Model Reinforcement Learning Agent Electric SHEEP Agent DREAM

January 24, 2023

Story Shaping: Teaching Agents Human-like Behavior with Stories
Xiangyu Peng, Christopher Cui, Wei Zhou, Renee Jia, Mark Riedl
Reinforcement Learning Agent BEHAVIOR Explanation Intrinsic Reward Written Story Reward Design Pedagogical Agent Narrative Designer Tacit Knowledge

December 15, 2022

Emergent Behaviors in Multi-Agent Target Acquisition
Piyush K. Sharma, Erin Zaroukian, Derrik E. Asher, Bryson Howell
Reinforcement Learning Multi Agent Multi Agent System Reinforcement Learning Agent Emergent Behavior

December 6, 2022

Reinforcement Learning for UAV control with Policy and Reward Shaping
Cristian Millán-Arias, Ruben Contreras, Francisco Cruz, Bruno Fernandes
Reinforcement Learning Unmanned Aerial Vehicle Autonomous Agent Reinforcement Learning Agent Reward Shaping Health Policy Recommendation Drone Control Interactive Reinforcement Learning

December 1, 2022

Modeling Mobile Health Users as Reinforcement Learning Agents
Eura Shin, Siddharth Swaroop, Weiwei Pan, Susan Murphy, Finale Doshi-Velez
Markov Decision Process Reinforcement Learning Agent Mobile Health Optimal Intervention