Evaluation of environmental impact upon human health with DeciMaS framework

Abstract

The article is dedicated to the problem of decision making in complex systems. Application of a novel interdisciplinary approach, which widely use intelligent agents is offered. The principal ideas of the novel approach are embodied into the DeciMaS framework, that offers a logical set of stages oriented to creation of decision support systems for complex problem management. The components of the DeciMaS framework and the way in which they are organized are introduced. Design and implementation of the system are discussed. The article demonstrates how the initial information is transformed into knowledge. Impact assessment upon human health evaluation is the case study, which is resolved by DeciMas framework. It includes creation of the meta-ontology. In addition, a multi-agent architecture for a decision support system is introduced. The sequence of the steps for the DeciMaS framework design with Prometheus Development Kit and its implementation with JACK Development Environment are presented as well. Finally, data and experiment results of data modeling, simulation, impact assessment, and decision generation are discussed.

Multi-Agent Based Simulation of Environmental Pollution Issues: A Review

“…To understand pollution and health related problems. [10], presents DeciMas, a hybrid agent based decision support system. It includes data mining technique to extract dependent variables.…”

A hybrid fuzzy intelligent agent-based system for stock price prediction

“…2 There are three agent teams defined within the proposed architecture: "Data preprocessing," "Function approximation," and "Knowledge presentation" agent teams (shown in Figure 4.). Agent teams synchronize the work of the system, execute plans in a concurrent mode, and strengthen the internal management by local decision making.…”

“…1 This problem is characterized by high complexity and a great number of interacting and highly interrelated economic, social, political, and even psychological components, and these factors interact with each other in a very complicated manner. 4 Multiagent systems are intelligent distributed approaches suited for applications that are modular, changeable, and complex. Nontraditional techniques from different domains can be effective in the case of complex systems, providing novel ways to generate decisions and find solutions.…”

“…Nontraditional techniques from different domains can be effective in the case of complex systems, providing novel ways to generate decisions and find solutions. 2 Because of these characteristics, multiagent based models are attracting significant attention in the study of financial markets. 4 Multiagent systems are intelligent distributed approaches suited for applications that are modular, changeable, and complex.…”

“…Nontraditional techniques from different domains can be effective in the case of complex systems, providing novel ways to generate decisions and find solutions. 2 The multiagent approach 3 is a suitable method that can help reduce the complexity of a system by creating independent components, which solve private subtasks that together achieve common goals. 4 Multiagent systems are intelligent distributed approaches suited for applications that are modular, changeable, and complex.…”