Constrained Reinforcement Learning with Average Reward Objective: Model-Based and Model-Free Algorithms

Author:   Vaneet Aggarwal ,  Washim Uddin Mondal ,  Qinbo Bai
Publisher:   now publishers Inc
ISBN:  

9781638283966


Pages:   116
Publication Date:   21 August 2024
Format:   Paperback
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Constrained Reinforcement Learning with Average Reward Objective: Model-Based and Model-Free Algorithms


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Overview

Reinforcement Learning (RL) serves as a versatile framework for sequential decision-making, finding applications across diverse domains such as robotics, autonomous driving, recommendation systems, supply chain optimization, biology, mechanics, and finance. The primary objective of these applications is to maximize the average reward. Real-world scenarios often necessitate adherence to specific constraints during the learning process. This monograph focuses on the exploration of various model-based and model-free approaches for Constrained RL within the context of average reward Markov Decision Processes (MDPs). The investigation commences with an examination of model-based strategies, delving into two foundational methods – optimism in the face of uncertainty and posterior sampling. Subsequently, the discussion transitions to parametrized model-free approaches, where the primal dual policy gradient-based algorithm is explored as a solution for constrained MDPs. The monograph provides regret guarantees and analyzes constraint violation for each of the discussed setups. For the above exploration, the authors assume the underlying MDP to be ergodic. Further, this monograph extends its discussion to encompass results tailored for weakly communicating MDPs, thereby broadening the scope of its findings and their relevance to a wider range of practical scenarios.

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Author:   Vaneet Aggarwal ,  Washim Uddin Mondal ,  Qinbo Bai
Publisher:   now publishers Inc
Imprint:   now publishers Inc
Weight:   0.176kg
ISBN:  

9781638283966


ISBN 10:   1638283966
Pages:   116
Publication Date:   21 August 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

1. Introduction 2. Model-Based RL 3. Parameterized Model-Free RL 4. Beyond Ergodic MDPs Acknowledgements References

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