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- Berger, Uta, et al.
(författare)
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Towards reusable building blocks for agent-based modelling and theory development
- 2024
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Ingår i: Environmental Modelling & Software. - 1364-8152 .- 1873-6726. ; 175
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Tidskriftsartikel (refereegranskat)abstract
- 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
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| 2. |
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| 3. |
- Scholz, Geeske, et al.
(författare)
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Social Agents? A Systematic Review of Social Identity Formalizations
- 2023
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Ingår i: JASSS. - : Journal of Artificial Societies and Social Simulation. - 1460-7425. ; 26:2
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Forskningsöversikt (refereegranskat)abstract
- Simulating collective decision-making and behaviour is at the heart of many agent-based models (ABMs). However, the representation of social context and its influence on an agent's behaviour remains challenging. Here, the Social Identity Approach (SIA) from social psychology offers a promising explanation, as it describes how people behave while being part of a group, how groups interact and how these interactions and ingroup norms can change over time. SIA is valuable for diverse application domains while being challenging to formalise. To address this challenge and enable modellers to learn from existing work, we take stock of ABM formalisations of SIA and present a systematic review of SIA in ABMs. Our results show a diversity of application areas and formalisations of (parts of) SIA without any converging practice towards a default formalisation. Models range from simple to (cognitively) rich, with a group of abstract models in the tradition of opinion dynamics employing SIA to specify group-based social influence. We also found some complex cognitive SIA formalisations incorporating contextual behaviour. Looking at the function of SIA in the models, representing collectives, modelling group-based social influence, and unpacking contextual behaviour stood out. Our review was also an inventory of the formalisation challenge attached to using a very promising social-psychological theory in ABMs, revealing a tendency for reference to domain-specific theories to remain vague.
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| 4. |
- Squazzoni, Flaminio, et al.
(författare)
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Computational Models that Matter During a Global Pandemic Outbreak : A Call to Action
- 2020
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Ingår i: JASSS. - : Journal of Artificial Societies and Social Simulation. - 1460-7425. ; 23:2
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Tidskriftsartikel (refereegranskat)abstract
- The COVID-19 pandemic is causing a dramatic loss of lives worldwide, challenging the sustainability of our health care systems, threatening economic meltdown, and putting pressure on the mental health of individuals (due to social distancing and lock-down measures). The pandemic is also posing severe challenges to the scientific community, with scholars under pressure to respond to policymakers' demands for advice despite the absence of adequate, trusted data. Understanding the pandemic requires fine-grained data representing specific local conditions and the social reactions of individuals. While experts have built simulation models to estimate disease trajectories that may be enough to guide decision-makers to formulate policy measures to limit the epidemic, they do not cover the full behavioural and social complexity of societies under pandemic crisis. Modelling that has such a large potential impact upon people's lives is a great responsibility. This paper calls on the scientific community to improve the transparency, access, and rigour of their models. It also calls on stakeholders to improve the rapidity with which data from trusted sources are released to the community (in a fully responsible manner). Responding to the pandemic is a stress test of our collaborative capacity and the social/economic value of research.
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| 5. |
- Wijermans, Nanda, 1981-, et al.
(författare)
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Agent decision-making : The Elephant in the Room - Enabling the justification of decision model fit in social-ecological models
- 2023
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Ingår i: Environmental Modelling & Software. - 1364-8152 .- 1873-6726. ; 170
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Tidskriftsartikel (refereegranskat)abstract
- Agent-based models are particularly suitable to reflect the dynamics of humans, nature, and their interactions, making them a crucial approach for understanding social-ecological systems. The formalisations of human decision-making are central to resulting model behaviours. Despite awareness of the complexity of human behaviour in social-ecological systems research, scholars tend to represent human decision-makers as simplified, perfectly informed rational optimisers, without explicitly considering the fit with decision context. Key reasons are a lacking uptake of social theories and insights. To advance, we need a practice of reflecting, sharing, and inquiring on the justification of the decision model fit with its context. This paper stimulates this practice by 1) supporting the justification of decision model (DM) fit by describing the DM landscape and providing guiding questions; and 2) by supporting researchers in considering alternative DMs through a survey-based impression of modeller practices, and through highlighting DM frontiers as inspiration for future research.
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