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• W2559788123 abstract "Using purely agent-based platforms for any kind of simulation requires to address the following challenges: 1) scalability; 2) efficient memory management; 3) modelling. While dedicated professional simulation tools usually provide rich domain libraries and advanced visualisation techniques, and support the simulation of large scenarios, they do not allow for 'agentisation' of single components. We are trying to bridge this gap by developing a distributed, scalable multi-agent simulation platform, MASeRaTi, addressing the three problems mentioned above. It allows to plug-in both dedicated simulation tools as well as the agentisation of certain components of the system. We describe the system architecture, which consists of a lightweight kernel and an agent-modelling layer, on top of which applications reside. An evaluation of the platform is provided by: 1) a proof-of-concept implementation of the well-known cow scenario used in the multi-agent programming contest; 2) experimentally investigating scalability in comparison to the Jason platform." @default.
• W2559788123 created "2016-12-16" @default.
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• W2559788123 date "2016-01-01" @default.
• W2559788123 modified "2023-09-24" @default.
• W2559788123 title "An architecture for scalable simulation of systems of cognitive agents" @default.
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• W2559788123 doi "https://doi.org/10.1504/ijaose.2016.080897" @default.
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