
The design of agent-based models (ABMs) is often ad-hoc when it comes to defining their scope. In order for the inclusion of features such as network structure, location, or dynamic change to be justified, their role in a model should be systematically analysed. We propose a mechanism to compare and assess the impact of such features. In particular we are using techniques from software engineering and semantics to support the development and assessment of ABMs, such as graph transformations as semantic representations for agent-based models, feature diagrams to identify ingredients under consideration, and extension relations between graph transformation systems to represent model fragments expressing features.
In Proceedings GaM 2017, arXiv:1712.08345
Social and Information Networks (cs.SI), FOS: Computer and information sciences, Other Computer Engineering, Logic and Foundations, Computer Science - Social and Information Networks, QA75.5-76.95, Software Engineering (cs.SE), Computer Science - Software Engineering, Algebra, Electronic computers. Computer science, QA1-939, Computer Science - Multiagent Systems, Other Mathematics, Other Computer Sciences, Mathematics, Multiagent Systems (cs.MA)
Social and Information Networks (cs.SI), FOS: Computer and information sciences, Other Computer Engineering, Logic and Foundations, Computer Science - Social and Information Networks, QA75.5-76.95, Software Engineering (cs.SE), Computer Science - Software Engineering, Algebra, Electronic computers. Computer science, QA1-939, Computer Science - Multiagent Systems, Other Mathematics, Other Computer Sciences, Mathematics, Multiagent Systems (cs.MA)
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