2020
DOI: 10.1016/j.promfg.2020.11.023
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A deployment-friendly decentralized scheduling approach for cooperative multi-agent systems in production systems

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Cited by 9 publications
(5 citation statements)
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“…To achieve this and to maximize system modularity and reconfigurability, we propose a multi-agent solution (see Fig. 3 a) which builds upon and expands the previous work by Egger et al 40 to embed sustainability aspects during planning and control. The proposed solution is based on a fully distributed architecture where intelligent actors can participate to the overall manufacturing capabilities, thus contributing to flexibility at a system-level , in a plug-n-play manner (provided they meet a commonly defined interface).…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…To achieve this and to maximize system modularity and reconfigurability, we propose a multi-agent solution (see Fig. 3 a) which builds upon and expands the previous work by Egger et al 40 to embed sustainability aspects during planning and control. The proposed solution is based on a fully distributed architecture where intelligent actors can participate to the overall manufacturing capabilities, thus contributing to flexibility at a system-level , in a plug-n-play manner (provided they meet a commonly defined interface).…”
Section: Methodsmentioning
confidence: 99%
“…Specifically, a production module might include different machines: typically, a principal one defining its main functionality (e.g., laser cutting), plus auxiliary ones (e.g., indicator lights). Following Egger et al 40 , agents schedule production tasks according to a message passing mechanism where messages are encoded as JSON strings defined according to FIPA protocols 41 . In particular, upon receiving a request to perform a certain task agents might do one of the following (see Fig.…”
Section: Methodsmentioning
confidence: 99%
“…Bu yeni araştırmalar, etmenlerin her birinin, problemlerin çözümü için diğer etmenler ile iş birliği yapacak ve iletişim kuracak şekilde tasarlanabilmesini [153,154] ve bu da daha verimli sistemler elde edilebilmesini sağlamıştır [155,156]. Üreticiler, ürün ve hizmetleri sağlamanın daha verimli yollarını araştırmasının bir sonucu olarak, yapay zeka teknolojisinde birçok farklı alanda kullanılmak üzere gelişme gösteren MAS'ler [154,[157][158][159] dinamik performansın değerlendirmesi, üretim süreçlerinin optimizasyonu, üretim kontrolü, pazarlama, sağlık hizmetleri, bilgi yönetimi ve oyun dahil olmak üzere bir çok alanda, özellikle takviyeli öğrenme etmenlerini (reinforcement learning agent) içeren bir çok uygulamada, günümüzde yaygın olarak kullanılmaktadır [160][161][162][163]. Bu yaklaşımda, tekrarlanan etkileşim yoluyla, etmen, öğrenilen stratejiye dayalı olarak en yüksek ödülü kazanacak şekilde tasarlanır.…”
Section: Platformların Iş Birliği (Platform Interoperability)unclassified
“…The prosumers coordinate the communication and work collaboratively; they are relatively independent and interconnected so that they can participate flexibly in daily transactions and operations of the power market. From the perspective of the operational control, the MAS is divided into a centralized and decentralized structures 17,18,19,20 . In the centralized structure, the prosumers in the VPP are divided into several groups.…”
Section: Interaction Of the Cyber‐physical System Networkmentioning
confidence: 99%