Features of Agent-based Models
This work addresses the problem of justifying feature inclusion in ABMs for researchers and practitioners, but it appears incremental as it applies existing techniques to a specific domain.
The paper tackles the ad-hoc design of agent-based models (ABMs) by proposing a mechanism to systematically analyze and compare the impact of features like network structure and location, using techniques from software engineering and semantics such as graph transformations and feature diagrams.
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.