Exploration Exploitation

The exploration-exploitation dilemma describes the fundamental challenge in decision-making systems of balancing the need to explore unknown options against the desire to exploit known, rewarding ones. Current research focuses on improving the efficiency of this trade-off across various domains, employing techniques like contextual bandits, Thompson sampling, and Bayesian optimization, often integrated with neural networks and graph neural networks to handle complex data and large action spaces. These advancements are significantly impacting fields like reinforcement learning, recommendation systems, and automated planning, leading to more efficient algorithms and improved performance in diverse applications.

Papers

September 7, 2024

LMGT: Optimizing Exploration-Exploitation Balance in Reinforcement Learning through Language Model Guided Trade-offs
Yongxin Deng, Xihe Qiu, Xiaoyu Tan, Wei Chu, Yinghui Xu
Reinforcement Learning Sparse Reward Industrial Recommender System Exploration Exploitation

August 19, 2024

The Exploration-Exploitation Dilemma Revisited: An Entropy Perspective
Renye Yan, Yaozhong Gan, You Wu, Ling Liang, Junliang Xing, Yimao Cai, Ru Huang
Reinforcement Learning Policy OpTimization Shannon Entropy Self Adaptation Exploration Exploitation

June 30, 2024

A Contextual Combinatorial Bandit Approach to Negotiation
Yexin Li, Zhancun Mu, Siyuan Qi
Bandit Feedback Negotiation Strategy Exploration Exploitation Iron Ore Negotiation Contextual Combinatorial Never Before Seen Negotiation Problem

May 26, 2024

Code Repair with LLMs gives an Exploration-Exploitation Tradeoff
Hao Tang, Keya Hu, Jin Peng Zhou, Sicheng Zhong, Wei-Long Zheng, Xujie Si, Kevin Ellis
Large Language Model Program Synthesis Program Repair Exploration Exploitation Breadth First Exploration Exploitation Tradeoff Invariant Synthesis

May 19, 2024

Budgeted Recommendation with Delayed Feedback
Kweiguu Liu, Setareh Maghsudi
Contextual Bandit Effective Recommendation Delayed Feedback Contextual Multi Armed Bandit Exploration Exploitation

April 26, 2024

Consolidating LAMA with Best-First Width Search
Augusto B. Corrêa, Jendrik Seipp
Heuristic Search Classical Planning Exploration Exploitation Heuristic Estimate

February 13, 2024

Amplifying Exploration in Monte-Carlo Tree Search by Focusing on the Unknown
Cedric Derstroff, Jannis Brugger, Jannis Blüml, Mira Mezini, Stefan Kramer, Kristian Kersting
Monte Carlo Tree Search Tree Search Exploration Performance Search Algorithm Exploration Exploitation

December 27, 2023

Foundations of Reinforcement Learning and Interactive Decision Making
Dylan J. Foster, Alexander Rakhlin
Reinforcement Learning Contextual Bandit Flawed Foundation Exploration Exploitation Interactive Decision Making Structured Bandit

December 26, 2023

A Bayesian Framework of Deep Reinforcement Learning for Joint O-RAN/MEC Orchestration
Fahri Wisnu Murti, Samad Ali, Matti Latva-aho
Deep Reinforcement Learning Open Radio Access Network Exploration Exploitation RAN Architecture Multi Access Edge Computing

December 2, 2023

Exploration-Exploitation Model of Moth-Inspired Olfactory Navigation
Teddy Lazebnik, Yiftach Golov, Roi Gurka, Ally Harari, Alex Liberzon
Exploration Exploitation Virtual Pheromone Direct Mating Inspired Navigation

October 10, 2023

Ensemble Active Learning by Contextual Bandits for AI Incubation in Manufacturing
Yingyan Zeng, Xiaoyu Chen, Ran Jin
Active Learning Contextual Bandit Manufacturing Industry Exploration Exploitation Shallow Learning Annotation Effort AI Prototyping

July 4, 2023

Approximate information for efficient exploration-exploitation strategies
Alex Barbier-Chebbah, Christian L. Vestergaard, Jean-Baptiste Masson
Multi Armed Bandit Average Approximation Exploration Exploitation Information Maximization Step Optimization

June 9, 2023

Fair yet Asymptotically Equal Collaborative Learning
Xiaoqiang Lin, Xinyi Xu, See-Kiong Ng, Chuan-Sheng Foo, Bryan Kian Hsiang Low
Reinforcement Learning Incremental Learning Collaborative Learning Incentive Mechanism Design Exploration Exploitation Fair Incentive

May 31, 2023

Representation-Driven Reinforcement Learning
Ofir Nabati, Guy Tennenholtz, Shie Mannor
Reinforcement Learning Contextual Bandit Exploration Exploitation Representation Optimization

May 15, 2023

Mastering the exploration-exploitation trade-off in Bayesian Optimization
Antonio Candelieri
Gaussian Process Bayesian Optimization Acquisition Function Exploration Exploitation Trade Exploration Exploitation

February 9, 2023

CLARE: Conservative Model-Based Reward Learning for Offline Inverse Reinforcement Learning
Sheng Yue, Guanbo Wang, Wei Shao, Zhaofeng Zhang, Sen Lin, Ju Ren, Junshan Zhang
Reward Function Inverse Reinforcement Learning Exploration Exploitation Reward Misspecification Conservative Reward

February 8, 2023

Learning How to Infer Partial MDPs for In-Context Adaptation and Exploration
Chentian Jiang, Nan Rosemary Ke, Hado van Hasselt
LeArning Abstract Markov Decision Process Environment Exploration Posterior Sampling Posterior Approximation Exploration Exploitation Contextual Adapter

September 15, 2022

Optimistic Curiosity Exploration and Conservative Exploitation with Linear Reward Shaping
Hao Sun, Lei Han, Rui Yang, Xiaoteng Ma, Jian Guo, Bolei Zhou
Reward Shaping Exploration Exploitation Curiosity Driven Exploration Value Based Deep Reinforcement Learning Conservative Prediction

August 16, 2022

A Policy Resonance Approach to Solve the Problem of Responsibility Diffusion in Multiagent Reinforcement Learning
Qingxu Fu, Tenghai Qiu, Jianqiang Yi, Zhiqiang Pu, Xiaolin Ai, Wanmai Yuan
Right Problem Single Agent Exploration Exploitation Responsibility Allocation

July 27, 2022

Adapting the Exploration-Exploitation Balance in Heterogeneous Swarms: Tracking Evasive Targets
Hian Lee Kwa, Victor Babineau, Julien Philippot, Roland Bouffanais
Multi Robot Multi Robot System Exploration Exploitation Heterogeneous Swarm