Lessons from a virtual slime: marginal mechanisms, minimal cognition and radical enactivism

2019 ◽  
Vol 28 (6) ◽  
pp. 453-464
Author(s):  
Lachlan Douglas Walmsley
Keyword(s):  
Physarum Polycephalum ◽  
Agent Model ◽  
Radical Enactivism ◽  
Slime Mould ◽  
Multi Agent ◽  
The Mind

Radical enactivism (REC) and similar embodied and enactive approaches to the mind deny that cognition is fundamentally representational, skull-bound and mechanistic in its organisation. In this article, I argue that modellers may still adopt a mechanistic strategy to produce explanations that are compatible with REC. This argument is scaffolded by a multi-agent model of the true slime mould Physarum polycephalum.

Research on multi-agent model based on track methodology of ontology building

2009 ◽  
Vol 29 (2) ◽  
pp. 412-415
Author(s):  
Qiang LU ◽  
Ming CHEN ◽  
Zhi-guang WANG
Keyword(s):  
Agent Model ◽  
Model Based ◽  
Multi Agent ◽  
Ontology Building

scholarly journals A Novel Multi-Agent Model for Robustness with Component Failure and Malware Propagation in Wireless Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4873
Author(s):  
Biao Xu ◽  
Minyan Lu ◽  
Hong Zhang ◽  
Cong Pan
Keyword(s):  
Wireless Sensor ◽  
Component Reliability ◽  
Agent Based ◽  
Agent Model ◽  
Cross Domain ◽  
Malware Propagation ◽  
Network Topologies ◽  
Multi Agent ◽  
Agent Characteristics ◽  
Information Domain

A wireless sensor network (WSN) is a group of sensors connected with a wireless communications infrastructure designed to monitor and send collected data to the primary server. The WSN is the cornerstone of the Internet of Things (IoT) and Industry 4.0. Robustness is an essential characteristic of WSN that enables reliable functionalities to end customers. However, existing approaches primarily focus on component reliability and malware propagation, while the robustness and security of cascading failures between the physical domain and the information domain are usually ignored. This paper proposes a cross-domain agent-based model to analyze the connectivity robustness of a system in the malware propagation process. The agent characteristics and transition rules are also described in detail. To verify the practicality of the model, three scenarios based on different network topologies are proposed. Finally, the robustness of the scenarios and the topologies are discussed.

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