Exploration Exploitation Trade

Exploration-exploitation trade-off research focuses on balancing the need to explore unknown areas of a search space against exploiting currently known promising regions to optimize a given objective. Current research emphasizes developing algorithms and model architectures (e.g., Bayesian optimization, reinforcement learning, multi-armed bandits) that dynamically adjust this balance, often incorporating uncertainty estimation and adaptive exploration strategies. This work is significant because efficient exploration-exploitation strategies are crucial for optimizing complex systems across diverse fields, including robotics, machine learning, and resource management, leading to improved efficiency and performance in various applications.

Papers

October 2, 2024

Diverse Expected Improvement (DEI): Diverse Bayesian Optimization of Expensive Computer Simulators
John Joshua Miller, Simon Mak, Benny Sun, Sai Ranjeet Narayanan, Suo Yang, Zongxuan Sun, Kenneth S. Kim, Chol-Bum Mike Kweon
Bayesian Optimization Surrogate Model Numerical Simulation Exploration Exploitation Trade Exploration Exploitation Tradeoff Expected Improvement

August 9, 2024

A Geometric Nash Approach in Tuning the Learning Rate in Q-Learning Algorithm
Kwadwo Osei Bonsu
Practical Algorithm Q Learning Nash Equilibrium Learning Rate Vector Valued Loss Minimization Exploration Exploitation Trade

July 6, 2024

Balancing Immediate Revenue and Future Off-Policy Evaluation in Coupon Allocation
Naoki Nishimura, Ken Kobayashi, Kazuhide Nakata
Exploration Exploitation Trade Capital Allocation Revenue Maximization

June 11, 2024

Fully Adaptive Regret-Guaranteed Algorithm for Control of Linear Quadratic Systems
Jafar Abbaszadeh Chekan, Cedric Langbort
External Control Adaptive Algorithm Exploration Exploitation Trade Adaptive Regret Quadratic System

May 28, 2024

Offline Oracle-Efficient Learning for Contextual MDPs via Layerwise Exploration-Exploitation Tradeoff
Jian Qian, Haichen Hu, David Simchi-Levi
Contextual Bandit Action Free Offline Exploration Exploitation Trade Near Optimal Algorithm Reward Free Reinforcement Learning Contextual Markov Decision Process Contextual MDPs

April 12, 2024

Auto-configuring Exploration-Exploitation Tradeoff in Evolutionary Computation via Deep Reinforcement Learning
Zeyuan Ma, Jiacheng Chen, Hongshu Guo, Yining Ma, Yue-Jiao Gong
Deep Reinforcement Learning Evolutionary Computation Deep Reinforcement Exploration Exploitation Trade Exploration Exploitation Tradeoff

March 1, 2024

Epsilon-Greedy Thompson Sampling to Bayesian Optimization
Bach Do, Taiwo Adebiyi, Ruda Zhang
Reinforcement Learning Bayesian Optimization Thompson Sampling Exploration Exploitation Trade Greedy Policy

October 30, 2023

DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization
Guowei Xu, Ruijie Zheng, Yongyuan Liang, Xiyao Wang, Zhecheng Yuan, Tianying Ji, Yu Luo, Xiaoyu Liu, Jiaxin Yuan, Pu Hua, Shuzhen Li, Yanjie Ze, Hal Daumé, Furong Huang, Huazhe Xu
Active Exploration Visual Reinforcement Learning Exploration Exploitation Trade Continuous Control Task

October 12, 2023

Dealing with uncertainty: balancing exploration and exploitation in deep recurrent reinforcement learning
Valentina Zangirolami, Matteo Borrotti
Reinforcement Learning Deep Reinforcement Learning High Uncertainty Anticipation Environment Exploration Autonomous Agent Real World eXploitation Exploration Exploitation Trade

October 5, 2023

LESSON: Learning to Integrate Exploration Strategies for Reinforcement Learning via an Option Framework
Woojun Kim, Jeonghye Kim, Youngchul Sung
Reinforcement Learning Exploration Exploitation Trade Exploration Strategy Instructional Design Option Learning

September 21, 2023

Incentivizing Massive Unknown Workers for Budget-Limited Crowdsensing: From Off-Line and On-Line Perspectives
Feng Li, Yuqi Chai, Huan Yang, Pengfei Hu, Lingjie Duan
Multi Armed Bandit Exploration Exploitation Trade Institutional Incentive Strategic Agent Unknown Unknown Mobile Crowdsensing

June 20, 2023

Reward Shaping via Diffusion Process in Reinforcement Learning
Peeyush Kumar
Reinforcement Learning Markov Decision Process Reward Shaping Stochastic Dynamical System Maximum Entropy Diffusion Process Exploration Exploitation Trade

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

May 5, 2023

Neural Exploitation and Exploration of Contextual Bandits
Yikun Ban, Yuchen Yan, Arindam Banerjee, Jingrui He
Environment Exploration Contextual Bandit Contextual Multi Armed Bandit Exploration Exploitation Trade Neural Bandit Neural Contextual Bandit

April 16, 2023

Dynamic Exploration-Exploitation Trade-Off in Active Learning Regression with Bayesian Hierarchical Modeling
Upala Junaida Islam, Kamran Paynabar, George Runger, Ashif Sikandar Iquebal
Active Learning Hierarchical Bayesian Exploration Exploitation Trade Approximate Bayesian Computation Exploration Exploitation Tradeoff Active Regression

March 15, 2023

Optimal Energy Management of Plug-in Hybrid Vehicles Through Exploration-to-Exploitation Ratio Control in Ensemble Reinforcement Learning
Bin Shuai, Min Hua, Yanfei Li, Shijin Shuai, Hongming Xu, Quan Zhou
Reinforcement Learning Energy Management Exploration Exploitation Trade Ensemble Deep Reinforcement Learning Hybrid Electric Vehicle Vehicle Energy

December 21, 2022

Neighboring state-based RL Exploration
Jeffery Cheng, Kevin Li, Justin Lin, Pedro Pachuca
Reinforcement Learning Discrete Environment Exploration Exploitation Trade Exploratory Action Free Exploration

November 30, 2022

Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off
Shaoyi Huang, Bowen Lei, Dongkuan Xu, Hongwu Peng, Yue Sun, Mimi Xie, Caiwen Ding
Sparse Model Sparse Training Dynamic Sparse Training Exploration Exploitation Trade

October 24, 2022

Exploration Exploitation Trade

Papers

Diverse Expected Improvement (DEI): Diverse Bayesian Optimization of Expensive Computer Simulators

A Geometric Nash Approach in Tuning the Learning Rate in Q-Learning Algorithm

Balancing Immediate Revenue and Future Off-Policy Evaluation in Coupon Allocation

Fully Adaptive Regret-Guaranteed Algorithm for Control of Linear Quadratic Systems

Offline Oracle-Efficient Learning for Contextual MDPs via Layerwise Exploration-Exploitation Tradeoff

Auto-configuring Exploration-Exploitation Tradeoff in Evolutionary Computation via Deep Reinforcement Learning

Epsilon-Greedy Thompson Sampling to Bayesian Optimization

DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization

Dealing with uncertainty: balancing exploration and exploitation in deep recurrent reinforcement learning

LESSON: Learning to Integrate Exploration Strategies for Reinforcement Learning via an Option Framework

Incentivizing Massive Unknown Workers for Budget-Limited Crowdsensing: From Off-Line and On-Line Perspectives

Reward Shaping via Diffusion Process in Reinforcement Learning

Mastering the exploration-exploitation trade-off in Bayesian Optimization

Neural Exploitation and Exploration of Contextual Bandits

Dynamic Exploration-Exploitation Trade-Off in Active Learning Regression with Bayesian Hierarchical Modeling

Optimal Energy Management of Plug-in Hybrid Vehicles Through Exploration-to-Exploitation Ratio Control in Ensemble Reinforcement Learning

Neighboring state-based RL Exploration

Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off

MEET: A Monte Carlo Exploration-Exploitation Trade-off for Buffer Sampling

Opportunistic Episodic Reinforcement Learning