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Item type:Publication, Access status: with files , Theory for and from agent-based modelling : insights from a virtual special issue and a visionThe Virtual Special Issue “Agents for Theory” discusses theory development using agent-based models (ABMs). The six contributions focus on how the word “theory” is used in the ABM literature, how reviews of ABMs should be conducted to gain general insights, how even the conceptualisation of ABMs can help to transform heuristic theories into scientific ones, how the context-dependent choice of decision models can be better justified, how reusable building blocks (RBBs) of ABMs could support theory development, and how a modular framework of RBBs can be used to identify general solutions. Overall, theories of decision making that go into ABMs and theories of system dynamics that come out of ABMs are interrelated, so the micro-macro perspective and the attempt to identify and reproduce patterns at both levels simultaneously is a way forward. Theory development requires clearer communication using a common language, reference to patterns, and more detailed model analysis and testing.Publicationtype: Journal Article25 217 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Towards reusable building blocks for agent-based modelling and theory development(Elsevier, 2024-04-01); ; ; ; Despite the increasing use of standards for documenting and testing agent-based models (ABMs) and sharing of open access code, most ABMs are still developed from scratch. This is not only inefficient, but also leads to ad hoc and often inconsistent implementations of the same theories in computational code and delays progress in the exploration of the functioning of complex social-ecological systems (SES). We argue that reusable building blocks (RBBs) known from professional software development can mitigate these issues. An RBB is a submodel that represents a particular mechanism or process that is relevant across many ABMs in an application domain, such as plant competition in vegetation models, or reinforcement learning in a behavioural model. RBBs need to be distinguished from modules, which represent entire subsystems and include more than one mechanism and process. While linking modules faces the same challenges as integrating different models in general, RBBs are “atomic” enough to be more easily re-used in different contexts. We describe and provide examples from different domains for how and why building blocks are used in software development, and the benefits of doing so for the ABM community and to individual modellers. We propose a template to guide the development and publication of RBBs and provide example RBBs that use this template. Most importantly, we propose and initiate a strategy for community-based development, sharing and use of RBBs. Individual modellers can have a much greater impact in their field with an RBB than with a single paper, while the community will benefit from increased coherence, facilitating the development of theory for both the behaviour of agents and the systems they form. We invite peers to upload and share their RBBs via our website - preferably referenced by a DOI (digital object identifier obtained e.g. via Zenodo). After a critical mass of candidate RBBs has accumulated, feedback and discussion can take place and both the template and the scope of the envisioned platform can be improved.Publicationtype: Journal ArticleScopus© Citations 2 34 81 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , From cases to general principles: A call for theory development through agent-based modeling(2019-02-01); ; ; Virtually all current major social and environmental challenges such as financial crises, migration, the erosion of democratic institutions, and the loss of biodiversity involve complex systems comprising decision-making, interacting, adaptive agents. To understand how such agent-based complex systems function and respond to change and disturbances, agent-based modeling (ABM) is increasingly recognized as the main way forward. Many motivating examples of agent-based models exist that are realistic enough to successfully support the management of complex systems, but these solutions are case-specific and contribute few general insights into the functioning of systems. General theory, though, is highly needed because we cannot model each system and question. Still, across disciplines, a critical mass of expertise has accumulated that could transform ABM into a more coherent and efficient approach to discover the functioning of complex social-economic-ecological systems. To this end, we need a cross-disciplinary discussion among researchers and a goal-oriented synthesis to identify the general principles and theories essential to improve our understanding and management of complex systems.Publicationtype: Journal Article242