AGENT-BASED INTERDISCIPLINARY FRAMEWORK FOR DECISION MAKING IN COMPLEX SYSTEMS

We offer a framework for the creation of decision support and expert systems for complex natural domains. This is due, on the one hand, to the numerous advantages of intelligent methods of data manipulation and, on the other hand, to the abilities of the computational agents to make decentralized decisions, which are crucial for complex systems modeling and simulation.In our approach, the qualitative improvement in decision making is obtained by using computational agents and interdisciplinary approach. The frameworks combines, on the one hand, the numerous advantages of intelligent methods for data manipulation and, on the other hand, the abilities of the computational agents to make decentralized decisions, which is crucial for complex system modeling and simulation. The approach contributes to decentralization and local decision making within the standard workflow. We demonstrate our framework in a case study and discuss obtained results.