Towards a Goal-Oriented Agent-Based Simulation Framework for High-Performance Computing

被引：1

作者：

Gnatyshak, Dmitry ^{[1
]}

Oliva-Felipe, Luis ^{[1
]}

Alvarez-Napagao, Sergio ^{[2
]}

Padget, Julian ^{[3
]}

Vazquez-Salceda, Javier ^{[1
]}

Garcia-Gasulla, Dario ^{[2
]}

Cortes, Ulises ^{[1
,2
]}

机构：

[1] Univ Politecn Cataluna, BarcelonaTECH UPC, C Jordi Girona 1-3, E-08034 Barcelona, Spain

[2] Barcelona Supercomp Ctr BSC, C Jordi Girona 1-3, E-08034 Barcelona, Spain

[3] Univ Bath, Dept Comp Sci, Bath BA2 7AY, Avon, England

来源：

ARTIFICIAL INTELLIGENCE RESEARCH AND DEVELOPMENT | 2019年 / 319卷

关键词：

agent-based simulation; high-performance computing; agent platform; multi-agent system; goal-oriented agent; PARALLEL;

D O I：

10.3233/FAIA190142

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Currently, agent-based simulation frameworks force the user to choose between simulations involving a large number of agents (at the expense of limited agent reasoning capability) or simulations including agents with increased reasoning capabilities (at the expense of a limited number of agents per simulation). This paper describes a first attempt at putting goal-oriented agents into large agent-based (micro-)simulations. We discuss a model for goal-oriented agents in High-Performance Computing (HPC) and then briefly discuss its implementation in Py-COMPSs (a library that eases the parallelisation of tasks) to build such a platform that benefits from a large number of agents with the capacity to execute complex cognitive agents.

引用

页码：329 / 338

页数：10

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