Agent-based approach to complex systems modeling

In this paper, we propose a method for detection of local system structures in a complex database. The complex database is viewed as consisting of mixed numeric and nominal attributes, and the local system structure as expressed by “if-then” rules. The detection of local system structures is an important task, and is concerned with inter-dependent issues. The issues involved in the detection of “if-then” rules include finding the objects that share common interests and then finding if-then rules that characterize those objects. To deal with these issues, an agent-based approach is proposed. Each agent has the role of collecting data points (objects) based on their similarity, for mixed data and detecting a rule. The similarity is introduced so that the agent can handle a mixed database. Each agent will occupy a part of the database as its territory according to the predefined algorithm with which agents try to expand or reduce their territories.