NDLI: MASE-BDI: agent-based simulator for environmental land change with efficient and parallel auto-tuning

Content Provider	Springer Nature Link
Author	C. Coelho, Cássio G. Abreu, Carolina G. Ramos, Rafael M. D. Mendes, Aldo H. Teodoro, George Ralha, Célia G.
Copyright Year	2016
Abstract	This paper presents an agent-based simulator for environmental land change that includes efficient and parallel auto-tuning. This simulator extends the Multi-Agent System for Environmental simulation (MASE) by introducing rationality to agents using a mentalistic approach—the Belief-Desire-Intention (BDI) model—and is thus named MASE-BDI. Because the manual tuning of simulation parameters is an error-prone, labour and computing intensive task, an auto-tuning approach with efficient multi-objective optimization algorithms is also introduced. Further, parallelization techniques are employed to speed up the auto-tuning process by deploying it in parallel systems. The MASE-BDI is compared to the MASE using the Brazilian Cerrado biome case. The MASE-BDI reduces the simulation execution times by at least 82 × and slightly improves the simulation quality. The auto-tuning algorithms, by evaluating less than 0.00115 % of a search space with 6 million parameter combinations, are able to quickly tune the simulation model, regardless of the objective used. Moreover, the experimental results show that executing the tuning in parallel leads to speedups of approximately 11 × compared to sequential execution in a hardware setting with 16-CPU cores.
Starting Page	904
Ending Page	922
Page Count	19
File Format	PDF
ISSN	0924669X
Journal	Applied Intelligence
Volume Number	45
Issue Number	3
e-ISSN	15737497
Language	English
Publisher	Springer US
Publisher Date	2016-06-04
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Belief-desire-intention Environmental simulation tool Land-use and cover change Multi-agent system Artificial Intelligence (incl. Robotics) Mechanical Engineering Manufacturing, Machines, Tools
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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