Modelling and simulation of complex systems: an approach based on multi-level agents

TL;DR

This paper presents a multi-level agent-based modeling framework for complex systems, emphasizing interactional and communicational levels inspired by cognitive engineering, with applications in manufacturing, urban transport, and epidemic detection.

Contribution

It introduces a four-behavior agent scale for modeling complex systems and discusses a general framework for multi-level agent-based simulation.

Findings

Developed a four-behavior agent scale for complex systems

Applied the framework to manufacturing, transport, and epidemic detection

Discussed ongoing work on multi-level agent models

Abstract

A complex system is made up of many components with many interactions. So the design of systems such as simulation systems, cooperative systems or assistance systems includes a very accurate modelling of interactional and communicational levels. The agent-based approach provides an adapted abstraction level for this problem. After having studied the organizational context and communicative capacities of agentbased systems, to simulate the reorganization of a flexible manufacturing, to regulate an urban transport system, and to simulate an epidemic detection system, our thoughts on the interactional level were inspired by human-machine interface models, especially those in "cognitive engineering". To provide a general framework for agent-based complex systems modelling, we then proposed a scale of four behaviours that agents may adopt in their complex systems (reactive, routine, cognitive, and collective). To complete the description of multi-level agent models, which is the focus of this paper, we illustrate our modelling and discuss our ongoing work on each level.