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Sebastian von Mammen
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Proceedings Papers
. isal2024, ALIFE 2024: Proceedings of the 2024 Artificial Life Conference7, (July 22–26, 2024) 10.1162/isal_a_00718
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Plants are complex organisms, showing collective adaptive behavior. Plant behavior is often defined by shoot growth, yet root systems exhibit equally complex, less visible, behaviors. Roots have to navigate in a particular environment, while optimizing nutrient and water uptake as well as avoiding exposure to harmful elements. In this paper, we introduce an interactive, agent-based simulation model of root growth. It supports the exploration of the interplay of different root models within different environments. To this end, we resort to Swarm Grammars (SGs) which combine the interactivity of spatial agents with the generative perspectives of LSystems. We pursue a point-based representation of the environment due to its versatility with respect to modeling and rendering possibilities. SGs and point-based environments are combined in a simulation that enables interactions between a user, agents and the environment at runtime. We validate the model by recreating and analysing several established root model configurations, and validate the benefits of the interactive simulation by an expert interview.
Proceedings Papers
. isal2023, ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life Conference102, (July 24–28, 2023) 10.1162/isal_a_00636
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We examine the learnability of emergent flocking behavior in boid simulations. To this end, we present (1) a detailed definition of the boid model, (2) a formulation such that model instances can be simulated efficiently, (3) metrics for training surrogate models, (4) and an evaluation of early training results. For this proof of concept, we focus on simple architectures like multi-layer perceptrons and graph neural networks. The performance of these models is comparable to simulations with an absolute error in the boid state of 5% in varying scenarios with varying interaction patterns and even surpasses the erroneous simulations for the prediction of formed flocks. By splitting the prediction task into a boid adjacency detection and a rule-application task, we observe that wrong interactions between boids only have a minor impact on the prediction results. Besides evaluating more complex models, we suggest focusing on either the detection of stable emergent states to predict them separately or on the understanding of dynamic transitions of groups that show emergent behavior.
Proceedings Papers
. ecal2017, ECAL 2017, the Fourteenth European Conference on Artificial Life475-482, (September 4–8, 2017) 10.1162/isal_a_078
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BOODLE (BiOlOgical DeveLopment Environment) is a long-term project to complement morphometric empirical studies in the field of developmental biology by means of interactive modelling and simulation techniques. BOODLE aims at providing viable behaviour models of cells that fit recorded time series of morphogenetic stages. This information is critical for driving empirical studies and for simulating the emergence of pathological abnormalities. In this paper, we present a BOODLE prototype that covers the whole functionality of the envisioned system. The application usage cycle starts with importing scan data of embryos of model organisms. Next, it allows the user/experimenter to work with the imported model, for instance to add meta data, to refine annotations, and even to automatically or manually populate the captured volumes with virtual cells. Finally, the user/experimenter is given the opportunity to run simulation experiments. To outline how the pipeline works in particular, we have setup a mockup toy experiment that optimises cell parameters such that a population of cells develops in accordance with several preset transient states. For all stages of the modelling and simulation process, BOODLE provides accessible interfaces and visualisations. These include visual programming and configuration of individual cells’ behaviours and physical properties. In this paper, we show how all these aspects together realise a prototype for a Biologist-in-the- Loop simulation for the creation, automated optimisation and analysis of cellular behaviour models.
Proceedings Papers
. ecal2015, ECAL 2015: the 13th European Conference on Artificial Life389-396, (July 20–24, 2015) 10.1162/978-0-262-33027-5-ch069
Proceedings Papers
. ecal2015, ECAL 2015: the 13th European Conference on Artificial Life320-324, (July 20–24, 2015) 10.1162/978-0-262-33027-5-ch060