Handling internal complexity in highly realistic agent-based models of human behaviour

Abstract

This article describes our work in progress and deals with methods and approaches for handling internal complexity emerging in highly realistic models of human behaviour. We present a new modelling approach to human decision making along with a conceptual design of several methods targeting selected aspects of complexity, such as the combinatorial explosion of action alternatives in rich environments, or the impact of ontological reasoning on human behaviour models that need to perform in real time. We illustrate our design in the context of the EDA project A-0938-RT-GC EUSAS, where we plan to implement it.