Towards A Novel Unified Framework for Developing Formal, Network and Validated Agent-Based Simulation Models of Complex Adaptive Systems

TL;DR

This paper proposes initial steps towards a unified framework for developing, comparing, and validating agent-based and network models of complex adaptive systems across scientific disciplines, enhancing interdisciplinary collaboration.

Contribution

It introduces a novel multi-level framework combining agent-based and network modeling approaches to facilitate cross-domain model development and validation.

Findings

Proposes a four-level usage framework for model development.

Enables multidisciplinary researchers to select appropriate modeling levels.

Facilitates better comparison and validation of models across domains.

Abstract

Literature on the modeling and simulation of complex adaptive systems (cas) has primarily advanced vertically in different scientific domains with scientists developing a variety of domain-specific approaches and applications. However, while cas researchers are inher-ently interested in an interdisciplinary comparison of models, to the best of our knowledge, there is currently no single unified framework for facilitating the development, comparison, communication and validation of models across different scientific domains. In this thesis, we propose first steps towards such a unified framework using a combination of agent-based and complex network-based modeling approaches and guidelines formulated in the form of a set of four levels of usage, which allow multidisciplinary researchers to adopt a suitable framework level on the basis of available data types, their research study objectives and expected outcomes, thus allowing them to better plan and conduct their respective re-search case studies.