Increasing Robustness of Agents' Decision-Making in Production Automation using Sanctioning

被引：0

作者：

Land, Kathrin ^{[1
]}

Nardin, Luis Gustavo ^{[2
]}

Vogel-Heuser, Birgit ^{[1
,3
]}

机构：

[1] Tech Univ Munich, Sch Engn & Design, Inst Automat & Informat Syst, Garching, Germany

[2] Univ Clermont Auvergne, Mines St Etienne, INP Clermont Auvergne, CNRS,UMR 6158,LIMOS, F-42023 St Etienne, France

[3] MDSI, Garching, Germany

来源：

2023 IEEE 21ST INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS, INDIN | 2023年

关键词：

production automation; multi-agent systems; decision-making; sanctioning; MODEL;

D O I：

10.1109/INDIN51400.2023.10217852

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Industry 4.0 requires high reconfigurability and flexibility of cyber-physical production systems (CPPS). Agent-based approaches are introduced to realize decentralized decision-making and flexibility within CPPS. Agents negotiate with each other regarding task allocation in production systems to achieve a global goal together. In non-deterministic systems, agents' decision-making can become inaccurate due to misalignment between the agents' beliefs and the actual state of the physical system they represent. (Un)Intentional misestimations can lead to non-optimal task allocation regarding the global system's goal. Additionally, decisions that benefit individual agents' goals, such as 'get all tasks', can contradict the global system's goal. In this paper, a sanctioning approach known from socio-technical systems is integrated into a non-deterministic production plant consisting of a process part and a logistics part to increase the robustness of agents' decision-making.

引用

页数：6

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