Rule-based approach to human-like decision simulating in agent-based modeling and simulation

In the paper we present results of our research related to the application of the method of declarative description of knowledge possessed by people making decisions, characteristic for rule-based systems in ABMS. The purpose of this study is to examine whether, based on knowledge built on declarations of people, it is possible to create an adequate rule-based model of agents. It has been established that only about 60% of respondents take decisions in accordance with the previously declared preferences. Nevertheless, in our opinion, the rule-based approach to the agent behavior modeling can provide good results by introducing a random factor in decision-making rules.