Features of Agent-based Models
Reiko Heckel (University of Leicester), Alexander Kurz (University of, Leicester), Edmund Chattoe-Brown (University of Leicester)

TL;DR
This paper introduces a systematic approach using software engineering techniques to compare and evaluate features like network structure and dynamics in agent-based models, improving their design and analysis.
Contribution
It proposes a novel framework employing graph transformations and feature diagrams to assess the impact of model features systematically.
Findings
Framework enables systematic feature comparison
Graph transformations represent model features effectively
Supports better design and validation of ABMs
Abstract
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.
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