“An ethnographic seduction”: how qualitative research and Agent-based models can benefit each other

We provide a general analytical framework for empirically informed agent-based simulations. This methodology provides present-day agent-based models with a sound and proper insight as to the behavior of social agents — an insight that statistical data often fall short of providing at least at a micro level and for hidden and sensitive populations. In the other direction, simulations can provide qualitative researchers in sociology, anthropology and other fields with valuable tools for: (a) testing the consistency and pushing the boundaries, of specific theoretical frameworks; (b) replicating and generalizing results; (c) providing a platform for cross-disciplinary validation of results

Towards an Architecture Proposal for Federation of Distributed DES Simulators

The simulation of large and complex Discrete Event Systems (DESs) increasingly imposes more demanding and urgent requirements on two aspects accepted as critical: (1) Intensive use of models of the simulated system that can be exploited in all phases of its life cycle where simulation can be used, and methodologies for these purposes; (2) Adaptation of simulation techniques to HPC infrastructures, as a method to improve simulation efficiency and to have scalable simulation environments. This paper proposes a Model Driven Engineering approach (MDE) based on Petri Nets (PNs) as formal model. This approach proposes a domain specific language based on modular PNs from which efficient distributed simulation code is generated in an automatic way. The distributed simulator is constructed over generic simulation engines of PNs, each one containing a data structure representing a piece of net and its simulation state. The simulation engine is called simbot and versions of it are available for different platforms. The proposed architecture allows, in an efficient way, a dynamic load balancing of the simulation work because the moving of PN pieces can be realized by moving a small number of integers representing the subnet and its state

Evolution of predator dispersal in relation to spatio-temporal prey dynamics : how not to get stuck in the wrong place!

Peer reviewedPublisher PD

Integrating BDI agents with Agent-based simulation platforms

Agent-Based Models (ABMs) is increasingly being used for exploring and supporting decision making about social science scenarios involving modelling of human agents. However existing agent-based simulation platforms (e.g., SWARM, Repast) provide limited support for the simulation of more complex cognitive agents required by such scenarios. We present a framework that allows Belief-Desire Intention (BDI) cognitive agents to be embedded in an ABM system. Architecturally, this means that the "brains" of an agent can be modelled in the BDI system in the usual way, while the "body" exists in the ABM system. The architecture is exible in that the ABM can still have non-BDI agents in the simulation, and the BDI-side can have agents that do not have a physical counterpart (such as an organisation). The framework addresses a key integration challenge of coupling event-based BDI systems, with time-stepped ABM systems. Our framework is modular and supports integration off-the-shelf BDI systems with off-the-shelf ABM systems. The framework is Open Source, and all integrations and applications are available for use by the modelling community

A Computational Approach to Understand In Vitro Alveolar Morphogenesis

Primary human alveolar type II (AT II) epithelial cells maintained in Matrigel cultures form alveolar-like cysts (ALCs) using a cytogenesis mechanism that is different from that of other studied epithelial cell types: neither proliferation nor death is involved. During ALC formation, AT II cells engage simultaneously in fundamentally different, but not fully characterized activities. Mechanisms enabling these activities and the roles they play during different process stages are virtually unknown. Identifying, characterizing, and understanding the activities and mechanisms are essential to achieving deeper insight into this fundamental feature of morphogenesis. That deeper insight is needed to answer important questions. When and how does an AT cell choose to switch from one activity to another? Why does it choose one action rather than another? We report obtaining plausible answers using a rigorous, multi-attribute modeling and simulation approach that leveraged earlier efforts by using new, agent and object-oriented capabilities. We discovered a set of cell-level operating principles that enabled in silico cells to self-organize and generate systemic cystogenesis phenomena that are quantitatively indistinguishable from those observed in vitro. Success required that the cell components be quasi-autonomous. As simulation time advances, each in silico cell autonomously updates its environment information to reclassify its condition. It then uses the axiomatic operating principles to execute just one action for each possible condition. The quasi-autonomous actions of individual in silico cells were sufficient for developing stable cyst-like structures. The results strengthen in silico to in vitro mappings at three levels: mechanisms, behaviors, and operating principles, thereby achieving a degree of validation and enabling answering the questions posed. We suggest that the in silico operating principles presented may have a biological counterpart and that a semiquantitative mapping exists between in silico causal events and in vitro causal events

Minimum Information About a Simulation Experiment (MIASE)

The original publication is available at www.ploscompbiol.orgReproducibility of experiments is a basic requirement for science. Minimum Information (MI) guidelines have proved a helpful means of enabling reuse of existing work in modern biology. The Minimum Information Required in the Annotation of Models (MIRIAM) guidelines promote the exchange and reuse of biochemical computational models. However, information about a model alone is not sufficient to enable its efficient reuse in a computational setting. Advanced numerical algorithms and complex modeling workflows used in modern computational biology make reproduction of simulations difficult. It is therefore essential to define the core information necessary to perform simulations of those models. The Minimum Information About a Simulation Experiment describes the minimal set of information that must be provided to make the description of a simulation experiment available to others. It includes the list of models to use and their modifications, all the simulation procedures to apply and in which order, the processing of the raw numerical results, and the description of the final output. MIASE allows for the reproduction of any simulation experiment. The provision of this information, along with a set of required models, guarantees that the simulation experiment represents the intention of the original authors. Following MIASE guidelines will thus improve the quality of scientific reporting, and will also allow collaborative, more distributed efforts in computational modeling and simulation of biological processes.The discussions that led to the definition of MIASE benefited from the support of a Japan Partnering Award by the UK Biotechnology and Biological Sciences Research Council. DW was supported by the Marie Curie program and by the German Research Association (DFG Research Training School ‘‘dIEM oSiRiS’’ 1387/1). This publication is based on work (EJC) supported in part by Award No KUK-C1-013-04, made by King Abdullah University of Science and Technology (KAUST). FTB acknowledges support by the NIH (grant 1R01GM081070- 01). JC is supported by the European Commission, DG Information Society, through the Seventh Framework Programme of Information and Communication Technologies, under the VPH NoE project (grant number 223920). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Publishers versio

Social Media, Gender and the Mediatisation of War: Exploring the German Armed Forces’ Visual Representation of the Afghanistan Operation on Facebook

Studies on the mediatisation of war point to attempts of governments to regulate the visual perspective of their involvements in armed conflict – the most notable example being the practice of ‘embedded reporting’ in Iraq and Afghanistan. This paper focuses on a different strategy of visual meaning-making, namely, the publication of images on social media by armed forces themselves. Specifically, we argue that the mediatisation of war literature could profit from an increased engagement with feminist research, both within Critical Security/Critical Military Studies and within Science and Technology Studies that highlight the close connection between masculinity, technology and control. The article examines the German military mission in Afghanistan as represented on the German armed forces’ official Facebook page. Germany constitutes an interesting, and largely neglected, case for the growing literature on the mediatisation of war: its strong antimilitarist political culture makes the representation of war particularly delicate. The paper examines specific representational patterns of Germany’s involvement in Afghanistan and discusses the implications which arise from what is placed inside the frame of visibility and what remains out of its view

At the Biological Modeling and Simulation Frontier

We provide a rationale for and describe examples of synthetic modeling and simulation (M&S) of biological systems. We explain how synthetic methods are distinct from familiar inductive methods. Synthetic M&S is a means to better understand the mechanisms that generate normal and disease-related phenomena observed in research, and how compounds of interest interact with them to alter phenomena. An objective is to build better, working hypotheses of plausible mechanisms. A synthetic model is an extant hypothesis: execution produces an observable mechanism and phenomena. Mobile objects representing compounds carry information enabling components to distinguish between them and react accordingly when different compounds are studied simultaneously. We argue that the familiar inductive approaches contribute to the general inefficiencies being experienced by pharmaceutical R&D, and that use of synthetic approaches accelerates and improves R&D decision-making and thus the drug development process. A reason is that synthetic models encourage and facilitate abductive scientific reasoning, a primary means of knowledge creation and creative cognition. When synthetic models are executed, we observe different aspects of knowledge in action from different perspectives. These models can be tuned to reflect differences in experimental conditions and individuals, making translational research more concrete while moving us closer to personalized medicine