scholarly journals AGENT-BASED MICRO-SIMULATIONS IN IMMUNOLOGY AND FINANCE

2006 ◽  
Vol 1 ◽  
pp. 319
Author(s):  
F. Castiglione
Keyword(s):  
Message Passing ◽  
Degrees Of Freedom ◽  
Computational Models ◽  
Physical Models ◽  
Discrete State ◽  
Agent Based ◽  
Computer Tools ◽  
New Class ◽  
Distributed Memory Machines ◽  
Tools And Techniques

In the search for computational models that help to understand the dynamics of Complex Systems, one can take a great advantage from the impressive acceleration of computer tools and techniques. In fact the very structure of computation on digital computers has inspired the introduction of new class of models (algorithms), where interaction among degrees of freedom are expressed by logical rules acting over a discrete state space – something much closer to "biological language" than to standard (floating point) physical models. Starting from the definitions of spin systems, with little changes we reach a definition a new model that is well suited to describe different simulation systems. Such class of models is can be considered a subclass of the Agent-Based systems in vogue nowadays. Moreover, we shortly describe two microscopic simulators of this type, which are being used to study microscopic phenomena in two completely different fields of application, namely immunology and finance. As a final remark, given the lattice representation of space, such computational-modeling paradigm is well suited for efficient and "relatively simple" parallelization. Indeed, both models have been implemented to run on parallel computers adopting the Message Passing paradigm for Distributed Memory machines.

scholarly journals Process Modeling and Simulation of Tableting—An Agent-Based Simulation Methodology for Direct Compression

Pharmaceutics ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 996
Author(s):  
Niels Lasse Martin ◽  
Ann Kathrin Schomberg ◽  
Jan Henrik Finke ◽  
Tim Gyung-min Abraham ◽  
Arno Kwade ◽  
...  
Keyword(s):  
Raw Materials ◽  
Pilot Scale ◽  
Physical Models ◽  
Agent Based Simulation ◽  
Validation Data ◽  
Agent Based ◽  
Industrial Processing ◽  
Digital Twins ◽  
Product And Process ◽  
The Impact

In pharmaceutical manufacturing, the utmost aim is reliably producing high quality products. Simulation approaches allow virtual experiments of processes in the planning phase and the implementation of digital twins in operation. The industrial processing of active pharmaceutical ingredients (APIs) into tablets requires the combination of discrete and continuous sub-processes with complex interdependencies regarding the material structures and characteristics. The API and excipients are mixed, granulated if required, and subsequently tableted. Thereby, the structure as well as the properties of the intermediate and final product are influenced by the raw materials, the parametrized processes and environmental conditions, which are subject to certain fluctuations. In this study, for the first time, an agent-based simulation model is presented, which enables the prediction, tracking, and tracing of resulting structures and properties of the intermediates of an industrial tableting process. Therefore, the methodology for the identification and development of product and process agents in an agent-based simulation is shown. Implemented physical models describe the impact of process parameters on material structures. The tablet production with a pilot scale rotary press is experimentally characterized to provide calibration and validation data. Finally, the simulation results, predicting the final structures, are compared to the experimental data.

scholarly journals A novel class of translationally invariant spin chains with long-range interactions

2020 ◽  
Vol 2020 (8) ◽  
Author(s):  
B. Basu-Mallick ◽  
F. Finkel ◽  
A. González-López
Keyword(s):  
Long Range ◽  
Degrees Of Freedom ◽  
Spin Chains ◽  
Open Chain ◽  
New Class ◽  
Spin Interactions ◽  
Long Range Interactions ◽  
Spin Reversal ◽  
Twisted Yangian ◽  
Internal Degrees Of Freedom

Abstract We introduce a new class of open, translationally invariant spin chains with long-range interactions depending on both spin permutation and (polarized) spin reversal operators, which includes the Haldane-Shastry chain as a particular degenerate case. The new class is characterized by the fact that the Hamiltonian is invariant under “twisted” translations, combining an ordinary translation with a spin flip at one end of the chain. It includes a remarkable model with elliptic spin-spin interactions, smoothly interpolating between the XXX Heisenberg model with anti-periodic boundary conditions and a new open chain with sites uniformly spaced on a half-circle and interactions inversely proportional to the square of the distance between the spins. We are able to compute in closed form the partition function of the latter chain, thereby obtaining a complete description of its spectrum in terms of a pair of independent su(1|1) and su(m/2) motifs when the number m of internal degrees of freedom is even. This implies that the even m model is invariant under the direct sum of the Yangians Y (gl(1|1)) and Y (gl(0|m/2)). We also analyze several statistical properties of the new chain’s spectrum. In particular, we show that it is highly degenerate, which strongly suggests the existence of an underlying (twisted) Yangian symmetry also for odd m.

scholarly journals Agent Based Models of Polymicrobial Biofilms and the Microbiome—A Review

2021 ◽  
Vol 9 (2) ◽  
pp. 417
Author(s):  
Sherli Koshy-Chenthittayil ◽  
Linda Archambault ◽  
Dhananjai Senthilkumar ◽  
Reinhard Laubenbacher ◽  
Pedro Mendes ◽  
...  
Keyword(s):  
Species Interactions ◽  
Computational Models ◽  
Human Microbiome ◽  
Agent Based Modeling ◽  
Autonomous Agent ◽  
Agent Based Models ◽  
Agent Based ◽  
Complex Interactions ◽  
Mucosal Surfaces ◽  
Living Organisms

The human microbiome has been a focus of intense study in recent years. Most of the living organisms comprising the microbiome exist in the form of biofilms on mucosal surfaces lining our digestive, respiratory, and genito-urinary tracts. While health-associated microbiota contribute to digestion, provide essential nutrients, and protect us from pathogens, disturbances due to illness or medical interventions contribute to infections, some that can be fatal. Myriad biological processes influence the make-up of the microbiota, for example: growth, division, death, and production of extracellular polymers (EPS), and metabolites. Inter-species interactions include competition, inhibition, and symbiosis. Computational models are becoming widely used to better understand these interactions. Agent-based modeling is a particularly useful computational approach to implement the various complex interactions in microbial communities when appropriately combined with an experimental approach. In these models, each cell is represented as an autonomous agent with its own set of rules, with different rules for each species. In this review, we will discuss innovations in agent-based modeling of biofilms and the microbiota in the past five years from the biological and mathematical perspectives and discuss how agent-based models can be further utilized to enhance our comprehension of the complex world of polymicrobial biofilms and the microbiome.

scholarly journals ABWiSE v1.0: Toward and Agent-Based Approach to Simulating Wildfire Spread

2021 ◽  
Author(s):  
Jeffrey Katan ◽  
Liliana Perez
Keyword(s):  
Human Life ◽  
Simulation Models ◽  
Empirical Models ◽  
Physical Models ◽  
Fire Behaviour ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Fire Front ◽  
Wildfire Simulation ◽  
Behaviour Simulation

Abstract. Wildfires are a complex phenomenon emerging from interactions between air, heat, and vegetation, and while they are an important component of many ecosystems’ dynamics, they pose great danger to those ecosystems, and human life and property. Wildfire simulation models are an important research tool that help further our understanding of fire behaviour and can allow experimentation without recourse to live fires. Current fire simulation models fit into two general categories: empirical models and physical models. We present a new modelling approach that uses agent-based modelling to combine the complexity found in physical models with the ease of computation of empirical models. Our model represents the fire front as a set of moving agents that respond to, and interact with, vegetation, wind, and terrain. We calibrate the model using two simulated fires and one real fire, and validate the model against another real fire and the interim behaviour of the real calibration fire. Our model successfully replicates these fires, with a Figure of Merit on par with simulations by the Prometheus simulation model. Our model is a stepping-stone in using agent-based modelling for fire behaviour simulation, as we demonstrate the ability of agent-based modelling to replicate fire behaviour through emergence alone.

scholarly journals A 3D Agent-Based Model of Lung Fibrosis

Symmetry ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 90
Author(s):  
Nicolò Cogno ◽  
Roman Bauer ◽  
Marco Durante
Keyword(s):  
Lung Fibrosis ◽  
Computational Models ◽  
Multiple Scales ◽  
Inflammatory Diseases ◽  
Cell Damage ◽  
Heterogeneous Systems ◽  
Chronic Obstructive ◽  
Agent Based Model ◽  
Agent Based ◽  
Radiation Induced

Understanding the pathophysiology of lung fibrosis is of paramount importance to elaborate targeted and effective therapies. As it onsets, the randomly accumulating extracellular matrix (ECM) breaks the symmetry of the branching lung structure. Interestingly, similar pathways have been reported for both idiopathic pulmonary fibrosis and radiation-induced lung fibrosis (RILF). Individuals suffering from the disease, the worldwide incidence of which is growing, have poor prognosis and a short mean survival time. In this context, mathematical and computational models have the potential to shed light on key underlying pathological mechanisms, shorten the time needed for clinical trials, parallelize hypotheses testing, and improve personalized drug development. Agent-based modeling (ABM) has proven to be a reliable and versatile simulation tool, whose features make it a good candidate for recapitulating emergent behaviors in heterogeneous systems, such as those found at multiple scales in the human body. In this paper, we detail the implementation of a 3D agent-based model of lung fibrosis using a novel simulation platform, namely, BioDynaMo, and prove that it can qualitatively and quantitatively reproduce published results. Furthermore, we provide additional insights on late-fibrosis patterns through ECM density distribution histograms. The model recapitulates key intercellular mechanisms, while cell numbers and types are embodied by alveolar segments that act as agents and are spatially arranged by a custom algorithm. Finally, our model may hold potential for future applications in the context of lung disorders, ranging from RILF (by implementing radiation-induced cell damage mechanisms) to COVID-19 and inflammatory diseases (such as asthma or chronic obstructive pulmonary disease).

Argument Structure Models and Visualization

2009 ◽  
pp. 75-82 ◽  
Author(s):  
Ephraim Nissan
Keyword(s):  
Artificial Intelligence ◽  
Argument Structure ◽  
Intelligent Systems ◽  
Computational Models ◽  
Ad Hoc ◽  
Wide Spectrum ◽  
Tutoring Systems ◽  
Computer Tools ◽  
Legal Evidence ◽  
Visualization Tools

In order to visualize argumentation, there exist tools from multimedia. The most advanced sides of computational modeling of arguments belong in models and tools upstream of visualization tools: the latter are an interface. Computer models of argumentation come in three categories: logic-based (highly theoretical), probablistic, and pragmatic ad hoc treatments. Theoretical formalisms of argumentation were developed by logicists within artificial intelligence (and were implemented and often can be reused outside the original applications), or then the formalisms are rooted in philosophers’ work. We cite some such work, but focus on tools that support argumentation visually. Argumentation turns out in a wide spectrum of everyday life situations, including professional ones. Computational models of argumentation have found application in tutoring systems, tools for marshalling legal evidence, and models of multiagent communication. Intelligent systems and other computer tools potentially stand to benefit as well. Multimedia are applied to argumentation (in visualization tools), and also are a promising field of application (in tutoring systems). The design of networks could potentially benefit, if communication is modeled using multiagent technology.

Agent-Based Modelling in Multicellular Systems Biology

2020 ◽  
pp. 369-389
Author(s):  
Sara Montagna ◽  
Andrea Omicini
Keyword(s):  
Developmental Biology ◽  
Drosophila Melanogaster ◽  
Systems Biology ◽  
Computational Models ◽  
The Self ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Multi Agent

This chapter aims at discussing the content of multi-agent based simulation (MABS) applied to computational biology i.e., to modelling and simulating biological systems by means of computational models, methodologies, and frameworks. In particular, the adoption of agent-based modelling (ABM) in the field of multicellular systems biology is explored, focussing on the challenging scenarios of developmental biology. After motivating why agent-based abstractions are critical in representing multicellular systems behaviour, MABS is discussed as the source of the most natural and appropriate mechanism for analysing the self-organising behaviour of systems of cells. As a case study, an application of MABS to the development of Drosophila Melanogaster is finally presented, which exploits the ALCHEMIST platform for agent-based simulation.

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