Reinforcement Learning System

Reinforcement learning (RL) systems aim to create agents that learn optimal behaviors through trial-and-error interactions with an environment, guided by reward signals. Current research emphasizes improving RL's efficiency and robustness, exploring novel architectures like ring attractors for improved action selection and domain-specific languages for more concise and interpretable solutions, as well as addressing challenges like safety, exploration under constraints, and the need for explainability. These advancements are driving applications in diverse fields, including robotics, game playing, recommender systems, and even ethical decision-making, highlighting RL's growing importance across scientific and practical domains.

Papers

October 4, 2024

Spatial-aware decision-making with ring attractors in reinforcement learning systems
Marcos Negre Saura, Richard Allmendinger, Theodore Papamarkou, Wei Pan
Reinforcement Learning Deep Reinforcement Learning Action Selection Reinforcement Learning System Global Attractor Neuronal Dynamic

September 26, 2024

MathDSL: A Domain-Specific Language for Concise Mathematical Solutions Via Program Synthesis
Sagnik Anupam, Maddy Bowers, Omar Costilla-Reyes, Armando Solar-Lezama
Domain Specific Action Space Program Synthesis Reinforcement Learning System

August 15, 2024

Physics-Guided Reinforcement Learning System for Realistic Vehicle Active Suspension Control
Anh N. Nhu, Ngoc-Anh Le, Shihang Li, Thang D. V. Truong
Reinforcement Learning Reinforcement Learning System Active Suspension Ride Comfort

May 24, 2024

Counterexample-Guided Repair of Reinforcement Learning Systems Using Safety Critics
David Boetius, Stefan Leue
Constrained Optimization Third Position Repair Reinforcement Learning System Counterexample Guided Repair Safety Critic

May 22, 2024

Lusifer: LLM-based User SImulated Feedback Environment for online Recommender systems
Danial Ebrat, Luis Rueda
User Behavior User Simulator Reinforcement Learning System Online Recommender System Learning Based Recommender System

November 15, 2023

Assessing the Robustness of Intelligence-Driven Reinforcement Learning
Lorenzo Nodari, Federico Cerutti
Native Robustness Reward Structure Reinforcement Learning System

August 3, 2023

Thespian: Multi-Character Text Role-Playing Game Agents
Christopher Cui, Xiangyu Peng, Mark Riedl
Agent System Text Based Game Role Playing Reinforcement Learning System Dungeon Dragon Character Aware Model

July 19, 2023

Technical Challenges of Deploying Reinforcement Learning Agents for Game Testing in AAA Games
Jonas Gillberg, Joakim Bergdahl, Alessandro Sestini, Andrew Eakins, Linus Gisslen
Reinforcement Learning Technical Challenge Reinforcement Learning System Game Testing Game Diplomacy

June 9, 2023

Explaining Reinforcement Learning with Shapley Values
Daniel Beechey, Thomas M. S. Smith, Özgür Şimşek
Reinforcement Learning Shapley Value Game Theory Cooperative Game Reinforcement Learning System

April 5, 2023

Constrained Exploration in Reinforcement Learning with Optimality Preservation
Peter C. Y. Chen
Reinforcement Learning Action Space Near Optimality Reinforcement Learning System Constrained Exploration

December 28, 2022

Don't do it: Safer Reinforcement Learning With Rule-based Guidance
Ekaterina Nikonova, Cheng Xue, Jochen Renz
Reinforcement Learning Reinforcement Learning System Epsilon Greedy Product Safety Idiom

November 21, 2022

Examining Policy Entropy of Reinforcement Learning Agents for Personalization Tasks
Anton Dereventsov, Andrew Starnes, Clayton G. Webster
Reinforcement Learning Agent Reinforcement Learning System Personalization Task Policy Entropy

November 7, 2022

Reward-Predictive Clustering
Lucas Lehnert, Michael J. Frank, Michael L. Littman
Reinforcement Learning Reward Model Reinforcement Learning System Semi Supervised Reward Predictive Clustering

September 2, 2022

Taming Multi-Agent Reinforcement Learning with Estimator Variance Reduction
Taher Jafferjee, Juliusz Ziomek, Tianpei Yang, Zipeng Dai, Jianhong Wang, Matthew Taylor, Kun Shao, Jun Wang, David Mguni
Multi Agent Reinforcement Learning Decentralized Training Multi Agent MuJoCo Multi Agent Actor Critic Reinforcement Learning System Tame Function

June 9, 2022

There is no Accuracy-Interpretability Tradeoff in Reinforcement Learning for Mazes
Yishay Mansour, Michal Moshkovitz, Cynthia Rudin
Reinforcement Learning Inherent Interpretability Maze Environment Reinforcement Learning System

June 1, 2022

Predecessor Features
Duncan Bailey, Marcelo G. Mattar
Reinforcement Learning Table Representation Reinforcement Learning System Novel Predecessor and Successor Recency Heuristic

May 17, 2022

Moral reinforcement learning using actual causation
Tue Herlau
Online Reinforcement Learning Causal Direction Actual Cause Moral Judgment Reinforcement Learning System

March 29, 2022

Demonstration-Bootstrapped Autonomous Practicing via Multi-Task Reinforcement Learning
Abhishek Gupta, Corey Lynch, Brandon Kinman, Garrett Peake, Sergey Levine, Karol Hausman
Reinforcement Learning Multi Task Reinforcement Learning Reinforcement Learning System Task Specific Policy

February 22, 2022

Continual Auxiliary Task Learning
Matthew McLeod, Chunlok Lo, Matthew Schlegel, Andrew Jacobsen, Raksha Kumaraswamy, Martha White, Adam White
Policy Learning Auxiliary Task Policy Algorithm Reinforcement Learning System Continual Task

February 11, 2022

Choices, Risks, and Reward Reports: Charting Public Policy for Reinforcement Learning Systems
Thomas Krendl Gilbert, Sarah Dean, Tom Zick, Nathan Lambert
Reinforcement Learning AI System Artificial General Intelligence Risk Sensitive Functional Mechanism Reward Report Value Laden Choice Reinforcement Learning System Public Policy

Reinforcement Learning System

Papers

Spatial-aware decision-making with ring attractors in reinforcement learning systems

MathDSL: A Domain-Specific Language for Concise Mathematical Solutions Via Program Synthesis

Physics-Guided Reinforcement Learning System for Realistic Vehicle Active Suspension Control

Counterexample-Guided Repair of Reinforcement Learning Systems Using Safety Critics

Lusifer: LLM-based User SImulated Feedback Environment for online Recommender systems

Assessing the Robustness of Intelligence-Driven Reinforcement Learning

Thespian: Multi-Character Text Role-Playing Game Agents

Technical Challenges of Deploying Reinforcement Learning Agents for Game Testing in AAA Games

Explaining Reinforcement Learning with Shapley Values

Constrained Exploration in Reinforcement Learning with Optimality Preservation

Don't do it: Safer Reinforcement Learning With Rule-based Guidance

Examining Policy Entropy of Reinforcement Learning Agents for Personalization Tasks

Reward-Predictive Clustering

Taming Multi-Agent Reinforcement Learning with Estimator Variance Reduction

There is no Accuracy-Interpretability Tradeoff in Reinforcement Learning for Mazes

Predecessor Features

Moral reinforcement learning using actual causation

Demonstration-Bootstrapped Autonomous Practicing via Multi-Task Reinforcement Learning

Continual Auxiliary Task Learning

Choices, Risks, and Reward Reports: Charting Public Policy for Reinforcement Learning Systems