scholarly journals Control and Optimization of Multi-Agent Systems and Complex Networks for Systems Engineering

Processes ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 2070
Author(s):  
Manuel Herrera ◽  
Marco Pérez-Hernández ◽  
Ajith Parlikad ◽  
Joaquín Izquierdo
Keyword(s):  
Complex Networks ◽  
Systems Engineering ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent ◽  
Engineered Systems

Systems engineering crosses multiple engineering disciplines for the design, control, and overall management of engineered systems [...]

scholarly journals Multi-Agent Systems and Complex Networks: Review and Applications in Systems Engineering

Processes ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 312 ◽  
Author(s):  
Manuel Herrera ◽  
Marco Pérez-Hernández ◽  
Ajith Kumar Parlikad ◽  
Joaquín Izquierdo
Keyword(s):  
Complex Networks ◽  
Systems Engineering ◽  
Future Research ◽  
Multi Agent Systems ◽  
Control Software ◽  
Research Directions ◽  
Supply Chain Networks ◽  
Agent Systems ◽  
Multi Agent ◽  
Future Research Directions

Systems engineering is an ubiquitous discipline of Engineering overlapping industrial, chemical, mechanical, manufacturing, control, software, electrical, and civil engineering. It provides tools for dealing with the complexity and dynamics related to the optimisation of physical, natural, and virtual systems management. This paper presents a review of how multi-agent systems and complex networks theory are brought together to address systems engineering and management problems. The review also encompasses current and future research directions both for theoretical fundamentals and applications in the industry. This is made by considering trends such as mesoscale, multiscale, and multilayer networks along with the state-of-art analysis on network dynamics and intelligent networks. Critical and smart infrastructure, manufacturing processes, and supply chain networks are instances of research topics for which this literature review is highly relevant.

scholarly journals A Review on Control and Optimisation of Multi-Agent Systems and Complex Networks for Systems Engineering

2020 ◽  
Author(s):  
Manuel Herrera ◽  
Marco Pérez-Hernández ◽  
Ajith Kumar Parlikad ◽  
Joaquín Izquierdo
Keyword(s):  
Complex Networks ◽  
Systems Engineering ◽  
Future Research ◽  
Multi Agent Systems ◽  
Control Software ◽  
Research Directions ◽  
Supply Chain Networks ◽  
Agent Systems ◽  
Multi Agent ◽  
Future Research Directions

Systems Engineering is an ubiquitous discipline of Engineering overlapping industrial, chemical, mechanical, manufacturing, control, software, electrical, and civil engineering. It provides tools for dealing with the complexity and dynamics related to the optimisation of physical, natural, and virtual systems management. This paper presents a review of how multi-agent systems and complex networks theory are brought together to address Systems Engineering and management problems. The review also encompasses current and future research directions both for theoretical fundamentals and applications in Industry. This is made by considering trends such as mesoscale, multiscale, and multilayer networks; along with the state-of-art analysis on network dynamics and intelligent networks. Critical and smart infrastructure, manufacturing processes, and supply chain networks are instances of research topics for which this literature review is highly relevant.

scholarly journals Using Agent-Based Methodologies in Healthcare Information Systems

2018 ◽  
Vol 18 (2) ◽  
pp. 123-132 ◽  
Author(s):  
Reem Abdalla ◽  
Alok Mishra
Keyword(s):  
Information Systems ◽  
Systems Engineering ◽  
Open Systems ◽  
Health Information System ◽  
Multi Agent Systems ◽  
Health Care Information ◽  
Systems Methodology ◽  
Agent Based ◽  
Agent Systems ◽  
Multi Agent

Abstract This paper carries out a comparative analysis to determine the advantages and the stages of two agent-based methodologies: Multi-agent Systems Engineering (MaSE) methodology, which is designed specifically for an agent-based and complete lifecycle approach, while also being appropriate for understanding and developing complex open systems; Agent Systems Methodology (ASEME) suggests a modular Multi-Agent System (MAS) development approach and uses the concept of intra-agent control. We also examine the strengths and weaknesses of these methodologies and the dependencies between their models and their processes. Both methodologies are applied to develop The Guardian Angle: Patient-Centered Health Information System (GA: PCHIS), which is an example of agent-based applications used to improve health care information systems.

Learning Systems Engineering

2005 ◽  
pp. 1820-1826
Author(s):  
Valentina Plekhanova
Keyword(s):  
Machine Learning ◽  
Systems Engineering ◽  
Autonomous Agents ◽  
Single Agent ◽  
Learning System ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Agent Learning ◽  
Multi Agent ◽  
Conventional Machine

Traditionally multi-agent learning is considered as the intersection of two subfields of artificial intelligence: multi-agent systems and machine learning. Conventional machine learning involves a single agent that is trying to maximise some utility function without any awareness of existence of other agents in the environment (Mitchell, 1997). Meanwhile, multi-agent systems consider mechanisms for the interaction of autonomous agents. Learning system is defined as a system where an agent learns to interact with other agents (e.g., Clouse, 1996; Crites & Barto, 1998; Parsons, Wooldridge & Amgoud, 2003). There are two problems that agents need to overcome in order to interact with each other to reach their individual or shared goals: since agents can be available/unavailable (i.e., they might appear and/or disappear at any time), they must be able to find each other, and they must be able to interact (Jennings, Sycara & Wooldridge, 1998).

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