Optimal Policy

Optimal policy research focuses on finding the best course of action within a given system, often modeled as a Markov Decision Process (MDP), to maximize a desired outcome (e.g., reward, efficiency). Current research emphasizes developing efficient algorithms, such as policy gradient methods and diffusion models, to solve these problems, particularly in complex settings with high dimensionality or uncertainty, often incorporating techniques like variance reduction and bias correction. These advancements are significant for various fields, including robotics, finance, and AI, enabling improved decision-making in scenarios ranging from controlling robots to optimizing resource allocation. The development of more efficient and robust algorithms for finding optimal policies continues to be a central focus.

Papers

October 2, 2023

Using Reinforcement Learning to Optimize Responses in Care Processes: A Case Study on Aggression Incidents
Bart J. Verhoef, Xixi Lu
Reinforcement Learning Case Study Markov Decision Process Q Learning Optimal Policy Communal Violence Healthcare Workflow High Performing Policy Response Evaluation

October 1, 2023

Thompson Exploration with Best Challenger Rule in Best Arm Identification
Jongyeong Lee, Junya Honda, Masashi Sugiyama
Optimal Policy Best Arm Identification Exploration Performance Bandit Model Two Armed

September 25, 2023

Sample Complexity of Neural Policy Mirror Descent for Policy Optimization on Low-Dimensional Manifolds
Zhenghao Xu, Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao
High Dimensional Policy Gradient Sample Complexity Optimal Policy Policy OpTimization Low Dimensional Manifold Policy Mirror Descent

September 22, 2023

Optimal Dynamic Fees for Blockchain Resources
Davide Crapis, Ciamac C. Moallemi, Shouqiao Wang
Optimal Policy Blockchain System Spillover Effect Dynamic Pricing Algorithm Dynamic Fee

September 15, 2023

Wasserstein Distributionally Robust Policy Evaluation and Learning for Contextual Bandits
Yi Shen, Pan Xu, Michael M. Zavlanos
LeArning Abstract Gradient Descent Optimal Policy Contextual Bandit Policy Evaluation Robust Optimization Distributionally Robust Optimization

September 12, 2023

Optimal and Fair Encouragement Policy Evaluation and Learning
Angela Zhou
LeArning Abstract Optimal Policy Fairness Constraint Proportional Fairness Dynamic Treatment Regime Preference Distribution Eligibility Criterion

September 11, 2023

Career Path Recommendations for Long-term Income Maximization: A Reinforcement Learning Approach
Spyros Avlonitis, Dor Lavi, Masoud Mansoury, David Graus
Q Learning Optimal Policy Career Counseling

September 6, 2023

Marketing Budget Allocation with Offline Constrained Deep Reinforcement Learning
Tianchi Cai, Jiyan Jiang, Wenpeng Zhang, Shiji Zhou, Xierui Song, Li Yu, Lihong Gu, Xiaodong Zeng, Jinjie Gu, Guannan Zhang
Reinforcement Learning Optimal Policy Value Based Reinforcement Learning Marketing Budget Allocation

September 1, 2023

Local and adaptive mirror descents in extensive-form games
Côme Fiegel, Pierre Ménard, Tadashi Kozuno, Rémi Munos, Vianney Perchet, Michal Valko
Optimal Policy Mirror Descent Extensive Form Game Online Mirror Descent Optimal Dependence

August 28, 2023

Rate-Optimal Policy Optimization for Linear Markov Decision Processes
Uri Sherman, Alon Cohen, Tomer Koren, Yishay Mansour
Optimal Policy Policy OpTimization Bandit Feedback Regret Minimization Episodic Markov Decision Process Regret Rate

August 16, 2023

Eliciting Risk Aversion with Inverse Reinforcement Learning via Interactive Questioning
Ziteng Cheng, Anthony Coache, Sebastian Jaimungal
Optimal Policy Inverse Reinforcement Learning Risk Aversion Risk Preference

August 7, 2023

Deep Q-Network for Stochastic Process Environments
Kuangheng He
Reinforcement Learning Optimal Policy Deep Q Network Stochastic Environment

July 26, 2023

Actions Speak What You Want: Provably Sample-Efficient Reinforcement Learning of the Quantal Stackelberg Equilibrium from Strategic Feedbacks
Siyu Chen, Mengdi Wang, Zhuoran Yang
Reinforcement Learning Optimal Policy Past Action Episodic Reinforcement Learning Sample Efficient Reinforcement Learning Entropy Regularized Feedback Mechanism Stackelberg Equilibrium

July 23, 2023

Optimal Control of Multiclass Fluid Queueing Networks: A Machine Learning Approach
Dimitris Bertsimas, Cheol Woo Kim
Optimal Policy Optimal Control Machine Learning Approach Control Policy

July 13, 2023

On the Effective Horizon of Inverse Reinforcement Learning
Yiqing Xu, Finale Doshi-Velez, David Hsu
Reinforcement Learning Optimal Policy Inverse Reinforcement Learning

July 11, 2023

Scaling Distributed Multi-task Reinforcement Learning with Experience Sharing
Sanae Amani, Khushbu Pahwa, Vladimir Braverman, Lin F. Yang
Optimal Policy Multiplicative Size Scaling Multi Task Reinforcement Learning Contextual Markov Decision Process Experience Sharing

July 7, 2023

Action-State Dependent Dynamic Model Selection
Francesco Cordoni, Alessio Sancetta
Optimal Policy Reinforcement Learning Algorithm Dynamic Programming Portfolio Selection

June 28, 2023

Sharper Model-free Reinforcement Learning for Average-reward Markov Decision Processes
Zihan Zhang, Qiaomin Xie
Optimal Policy Model Free Model Free Reinforcement Learning Average Reward Markov Decision Process

June 24, 2023

Decision-Dependent Distributionally Robust Markov Decision Process Method in Dynamic Epidemic Control
Jun Song, William Yang, Chaoyue Zhao
Markov Decision Process Optimal Policy Pandemic Control Distributionally Robust Markov Decision Process

June 22, 2023

Pure Exploration in Bandits with Linear Constraints
Emil Carlsson, Debabrota Basu, Fredrik D. Johansson, Devdatt Dubhashi
Optimal Policy Game Theoretic Optimal Algorithm Pure Exploration Linear Constraint

Optimal Policy

Papers

Using Reinforcement Learning to Optimize Responses in Care Processes: A Case Study on Aggression Incidents

Thompson Exploration with Best Challenger Rule in Best Arm Identification

Sample Complexity of Neural Policy Mirror Descent for Policy Optimization on Low-Dimensional Manifolds

Optimal Dynamic Fees for Blockchain Resources

Wasserstein Distributionally Robust Policy Evaluation and Learning for Contextual Bandits

Optimal and Fair Encouragement Policy Evaluation and Learning

Career Path Recommendations for Long-term Income Maximization: A Reinforcement Learning Approach

Marketing Budget Allocation with Offline Constrained Deep Reinforcement Learning

Local and adaptive mirror descents in extensive-form games

Rate-Optimal Policy Optimization for Linear Markov Decision Processes

Eliciting Risk Aversion with Inverse Reinforcement Learning via Interactive Questioning

Deep Q-Network for Stochastic Process Environments

Actions Speak What You Want: Provably Sample-Efficient Reinforcement Learning of the Quantal Stackelberg Equilibrium from Strategic Feedbacks

Optimal Control of Multiclass Fluid Queueing Networks: A Machine Learning Approach

On the Effective Horizon of Inverse Reinforcement Learning

Scaling Distributed Multi-task Reinforcement Learning with Experience Sharing

Action-State Dependent Dynamic Model Selection

Sharper Model-free Reinforcement Learning for Average-reward Markov Decision Processes

Decision-Dependent Distributionally Robust Markov Decision Process Method in Dynamic Epidemic Control

Pure Exploration in Bandits with Linear Constraints