An implementation of framework of business intelligence for agent-based simulation

Abstract

Integrated environmental modeling approaches, especially agent-based modeling ones, are increasingly used in large-scale decision support systems. A major consequence of this trend is the manipulation and generation of a huge amount of data in simulations, which require to be efficiently managed. In this paper, we present a Combination Framework of Business intelligence solution and Multi-agent platform (CFBM) and its implementation on the GAMA platform. CFBM is a logical framework dedicated to the management of the input and output data of simulations, as well as the corresponding empirical datasets in an integrated way and the analysis on integrated data, which we propose as a coupling of two major methodologies: Multi-Agent Simulation (MAS) on one hand and Business Intelligence (BI) solution on the other. An integrated model of a surveillance network and Brown Plant Hopper (BPH) invasion is presented. This model is used throughout the paper as a case study of CFBM regarding to the database accesses, the integration of internal and external processing, and the model validation tasks. We show how the proposed combination framework can be an appropriate choice for all decision-support systems with a huge data, hence the modelers can be also encouraged to develop the big model in a large scale.