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Sökning: WFRF:(Grimm Volker)

  • Resultat 1-10 av 16
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1.
  • An, Li, et al. (författare)
  • Challenges, tasks, and opportunities in modeling agent-based complex systems
  • 2021
  • Ingår i: Ecological Modelling. - : Elsevier BV. - 0304-3800 .- 1872-7026. ; 457
  • Forskningsöversikt (refereegranskat)abstract
    • Humanity is facing many grand challenges at unprecedented rates, nearly everywhere, and at all levels. Yet virtually all these challenges can be traced back to the decision and behavior of autonomous agents that constitute the complex systems under such challenges. Agent-based modeling has been developed and employed to address such challenges for a few decades with great achievements and caveats. This article reviews the advances of ABM in social, ecological, and socio-ecological systems, compare ABM with other traditional, equation-based models, provide guidelines for ABM novice, modelers, and reviewers, and point out the challenges and impending tasks that need to be addressed for the ABM community. We further point out great opportunities arising from new forms of data, data science and artificial intelligence, showing that agent behavioral rules can be derived through data mining and machine learning. Towards the end, we call for a new science of Agent-based Complex Systems (ACS) that can pave an effective way to tackle the grand challenges.
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  • An, Li, et al. (författare)
  • Modeling agent decision and behavior in the light of data science and artificial intelligence
  • 2023
  • Ingår i: Environmental Modelling & Software. - 1364-8152 .- 1873-6726. ; 166
  • Tidskriftsartikel (refereegranskat)abstract
    • Agent-based modeling (ABM) has been widely used in numerous disciplines and practice domains, subject to many eulogies and criticisms. This article presents key advances and challenges in agent-based modeling over the last two decades and shows that understanding agents' behaviors is a major priority for various research fields. We demonstrate that artificial intelligence and data science will likely generate revolutionary impacts for science and technology towards understanding agent decisions and behaviors in complex systems. We propose an innovative approach that leverages reinforcement learning and convolutional neural networks to equip agents with the intelligence of self-learning their behavior rules directly from data. We call for further developments of ABM, especially modeling agent behaviors, in the light of data science and artificial intelligence.
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  • Ayllón, Daniel, et al. (författare)
  • Keeping modelling notebooks with TRACE : Good for you and good for environmental research and management support
  • 2021
  • Ingår i: Environmental Modelling & Software. - : Elsevier BV. - 1364-8152 .- 1873-6726. ; 136
  • Tidskriftsartikel (refereegranskat)abstract
    • The acceptance and usefulness of simulation models are often limited by the efficiency, transparency, reproducibility, and reliability of the modelling process. We address these issues by suggesting that modellers (1) “trace” the iterative modelling process by keeping a modelling notebook corresponding to the laboratory notebooks used by empirical researchers, (2) use a standardized notebook structure and terminology based on the existing TRACE documentation framework, and (3) use their notebooks to compile TRACE documents that supplement publications and reports. These practices have benefits for model developers, users, and stakeholders: improved and efficient model design, analysis, testing, and application; increased model acceptance and reuse; and replicability and reproducibility of the model and the simulation experiments. Using TRACE terminology and structure in modelling notebooks facilitates production of TRACE documents. We explain the rationale of TRACE, provide example TRACE documents, and suggest strategies for keeping “TRACE Modelling Notebooks.”
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  • Banitz, Thomas, et al. (författare)
  • Model-derived causal explanations are inherently constrained by hidden assumptions and context : The example of Baltic cod dynamics
  • 2022
  • Ingår i: Environmental Modelling & Software. - : Elsevier BV. - 1364-8152 .- 1873-6726. ; 156
  • Tidskriftsartikel (refereegranskat)abstract
    • Models are widely used for investigating cause-effect relationships in complex systems. However, often different models yield diverging causal claims about specific phenomena. Therefore, critical reflection is needed on causal insights derived from modeling. As an example, we here compare ecological models dealing with the dynamics and collapse of cod in the Baltic Sea. The models addressed different specific questions, but also vary widely in system conceptualization and complexity. With each model, certain ecological factors and mechanisms were analyzed in detail, while others were included but remained unchanged, or were excluded. Model-based causal analyses of the same system are thus inherently constrained by diverse implicit assumptions about possible determinants of causation. In developing recommendations for human action, awareness is needed of this strong context dependence of causal claims, which is often not entirely clear. Model comparisons can be supplemented by integrating findings from multiple models and confronting models with multiple observed patterns.
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6.
  • Banitz, Thomas, et al. (författare)
  • Visualization of causation in social-ecological systems
  • 2022
  • Ingår i: Ecology and Society. - : Resilience Alliance, Inc.. - 1708-3087. ; 27:1
  • Tidskriftsartikel (refereegranskat)abstract
    • In social-ecological systems (SES), where social and ecological processes are intertwined, phenomena are usually complex and involve multiple interdependent causes. Figuring out causal relationships is thus challenging but needed to better understand and then affect or manage such systems. One important and widely used tool to identify and communicate causal relationships is visualization. Here, we present several common visualization types: diagrams of objects and arrows, X-Y plots, and X-Y-Z plots, and discuss them in view of the particular challenges of visualizing causation in complex systems such as SES. We use a simple demonstration model to create and compare exemplary visualizations and add more elaborate examples from the literature. This highlights implicit strengths and limitations of widely used visualization types and facilitates adequate choices when visualizing causation in SES. Thereupon, we recommend further suitable ways to account for complex causation, such as figures with multiple panels, or merging different visualization types in one figure. This provides caveats against oversimplifications. Yet, any single figure can rarely capture all relevant causal relationships in an SES. We therefore need to focus on specific questions, phenomena, or subsystems, and often also on specific causes and effects that shall be visualized. Our recommendations allow for selecting and combining visualizations such that they complement each other, support comprehensive understanding, and do justice to the existing complexity in SES. This lets visualizations realize their potential and play an important role in identifying and communicating causation.
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  • Berger, Uta, et al. (författare)
  • Towards reusable building blocks for agent-based modelling and theory development
  • 2024
  • Ingår i: Environmental Modelling & Software. - 1364-8152 .- 1873-6726. ; 175
  • 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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8.
  • Dornelles, Andre Z., et al. (författare)
  • Towards a bridging concept for undesirable resilience in social-ecological systems
  • 2020
  • Ingår i: Global Sustainability. - : Cambridge University Press (CUP). - 2059-4798. ; 3
  • Tidskriftsartikel (refereegranskat)abstract
    • Non-technical summary Resilience is a cross-disciplinary concept that is relevant for understanding the sustainability of the social and environmental conditions in which we live. Most research normatively focuses on building or strengthening resilience, despite growing recognition of the importance of breaking the resilience of, and thus transforming, unsustainable social-ecological systems. Undesirable resilience (cf. lock-ins, social-ecological traps), however, is not only less explored in the academic literature, but its understanding is also more fragmented across different disciplines. This disparity can inhibit collaboration among researchers exploring interdependent challenges in sustainability sciences. In this article, we propose that the term lock-in may contribute to a common understanding of undesirable resilience across scientific fields. Technical summary Resilience is an extendable concept that bridges the social and life sciences. Studies increasingly interpret resilience normatively as a desirable property of social-ecological systems, despite growing awareness of resilient properties leading to social and ecological degradation, vulnerability or barriers that hinder sustainability transformations (i.e., 'undesirable' resilience). This is the first study to qualify, quantify and compare the conceptualization of 'desirable' and 'undesirable' resilience across academic disciplines. Our literature analysis found that various synonyms are used to denote undesirable resilience (e.g., path dependency, social-ecological traps, institutional inertia). Compared to resilience as a desirable property, research on undesirable resilience is substantially less frequent and scattered across distinct scientific fields. Amongst synonyms for undesirable resilience, the term lock-in is more frequently and evenly used across academic disciplines. We propose that lock-in therefore has the potential to reconcile diverse interpretations of the mechanisms that constrain system transformation - explicitly and coherently addressing characteristics of reversibility and plausibility - and thus enabling integrative understanding of social-ecological system dynamics. Social media summary 'Lock-in' as a bridging concept for interdisciplinary understanding of barriers to desirable sustainability transitions.
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