The Impact of Communication and Memory in State-Based Potential Game-based Distributed Optimization-Reference-Cited by-同舟云学术

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The Impact of Communication and Memory in State-Based Potential Game-based Distributed Optimization

Published:2022-07-25 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 20th International Conference on Industrial Informatics (INDIN)
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Author:

Yuwono Steve¹,Schwung Andreas¹,Schwung Dorothea²

Affiliation:

1. South Westphalia University of Applied Sciences,Department of Automation Technology and Learning Systems,Soest,Germany

2. Hochschule Düsseldorf University of Applied Sciences,Department of Artificial Intelligence and Data Science,Düsseldorf,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9975846/9976066/09976106.pdf?arnumber=9976106

Reference18 articles.

1. Potential Games

2. Cooperative Control and Potential Games

3. A Model-Free Approach to Wind Farm Control Using Game Theoretic Methods

4. A Comprehensive Survey of Potential Game Approaches to Wireless Networks

5. Self Learning in Flexible Manufacturing Units: A Reinforcement Learning Approach

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1. MLPro-MPPS - A Versatile and Configurable Production Systems Simulator in Python;2023 IEEE 2nd Industrial Electronics Society Annual On-Line Conference (ONCON);2023-12-08

2. Model-based learning on state-based potential games for distributed self-optimization of manufacturing systems;Journal of Manufacturing Systems;2023-12

3. A Model-Based Deep Learning Approach for Self-Learning in Smart Production Systems;2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA);2023-09-12

4. Model Predictive Control with Adaptive PLC-based Policy on Low Dimensional State Representation for Industrial Applications;2023 31st Mediterranean Conference on Control and Automation (MED);2023-06-26

5. MLPro-MPPS—A high-performance simulation framework for customizable production systems;Software Impacts;2023-05

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