Epistemology of modeling and simulation

Tolk, Andreas; Ihrig, Martin; Page, Ernest H.; Szabo, Claudia; Heath, Brian L.; Padilla, José J.; Suarez, E. Dante; Weirich, Paul; Yılmaz, Levent

doi:10.1109/wsc.2013.6721504

Cited by 20 publications

(7 citation statements)

References 38 publications

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“…Fundamental system of definitions can build up a field of study as related to other field(s) or standing on its own based on a new origin. Tolk et al (2013) discussed whether current philosophy of science is sufficient or a new pragmatic philosophy of simulation is needed. Modeling and Simulation (M&S) is a multi-disciplinary arena with multiple, both qualitative and quantitative, methods used for various purposes.…”

Section: Philosophical Foundations For Hybrid (Balaban)mentioning

confidence: 99%

Hybrid Simulation: Historical lessons, present challenges and futures

Eldabi

Balaban

Brailsford

et al. 2016

2016 Winter Simulation Conference (WSC)

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Hybrid simulation comes in many shapes and forms. It has been argued by many researchers that hybrid simulation provides a better insight of the system in hand as it allows modelers to assess its inherent problems from different dimensions. As a result Hybrid Simulation is becoming an important field within the Modeling and Simulation arena. Yet we find that there no clear and cohesive definition for it. Therefore, this panel paper aims to explore the concept of Hybrid Simulation and its progression through the years. In doing so, we hope to lay out the underpinnings of a structured Hybrid Simulation approach by providing historical narratives of the origins of hybrid models; the current challenges expressed by scholars; and future studies to ensure more focused development of a comprehensive methodology for Hybrid Simulation.

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Section: Philosophical Foundations For Hybrid (Balaban)mentioning

confidence: 99%

Hybrid Simulation: Historical lessons, present challenges and futures

Eldabi

Balaban

Brailsford

et al. 2016

2016 Winter Simulation Conference (WSC)

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“…Frank and Troitzsch 2005;Chattoe-Brown 2013;Tolk et al 2013) still need to be thoroughly discussed within the discipline. It is only when simulation enters the mainstream of archaeological practice and university curricula that the full potential of the technique can be realised and better adapted to the specifics of our discipline.…”

Section: Discussionmentioning

confidence: 99%

So You Think You Can Model? A Guide to Building and Evaluating Archaeological Simulation Models of Dispersals

Romanowska¹

2015

Human Biology

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With the current surge of simulation studies in archaeology there is a growing concern for the lack of engagement and feedback between modellers and domain specialists. To facilitate this dialogue I present a compact guide to the simulation modelling process applied to a common research topic and the focus of this special issue of Human Biology-human dispersals. The process of developing a simulation is divided into nine steps grouped in three phases. ThePre-print version. Visit digitalcommons.wayne.edu/humbiol after publication for the final version.conceptual phase consists of identifying research questions (step 1) and finding the most suitable method (step 2), designing the general framework and the resolution of the simulation (step 3) and then by filling in that framework with the modelled entities and the rules of interactions (step 4). This is followed by the technical phase of coding and testing (step 5), parameterising the simulation (step 6) and running it (step 7). In the final phase the results of the simulation are analysed and re-contextualised (step 8) and the findings of the model are disseminated in publications and code repositories (step 9). Each step will be defined and characterised and then illustrated with examples of published human dispersals simulation studies. While not aiming to be a comprehensive textbookstyle guide to simulation, this overview of the process of modelling human dispersals should arm any non-modeller with enough understanding to evaluate the quality, strengths and weaknesses of any particular archaeological simulation and provide a starting point for further exploration of this common scientific tool.All archaeologists start modelling the moment they step out of the excavation trench. We interpret the individual finds (e.g., pots, skeletons, buildings etc.) within certain frameworks (e.g., pottery typologies, bone taxonomies, architectural types etc.) and analyse sets of finds to detect population level patterns (e.g., cultural similarities, age profiles of bone assemblages, urbanPre-print version. Visit digitalcommons.wayne.edu/humbiol after publication for the final version. development, etc.) with strict analytical rigour. However, the interpretations of these patterns in terms of human behaviour and causality are predominantly built using natural language, i.e. they are constructed in the form of conceptual models that hypothesise which causal mechanisms might have led from actions of individual actors (the owners of pots, users of skeletons and inhabitants of buildings) to the detected population-level patterns. These causal relationships are often described as, for example, "culture A influenced culture B," "the dispersal reached area C," or "population D outcompeted population E." Although inferences like these are made on the basis of rigorously collected and analysed data, and are commonly built upon extensive research and a good understanding of multiple strands of evidence, they nevertheless represent a thought experiment and are therefore limited ...

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“…When fluidization is total and the nets are considered under infinite server semantics, the relaxed models constitute a subclass of piecewise affine systems, more precisely with a polytopic partition in the state domain and continuity in their derivatives (the applicability of the fluidization of PN models depends on the particular properties under study and on the structure of the system under consideration [Silva, 2016]). Because I frequently hear about simulation with some reluctance, you can simply interpret this keynote as a praise for simulation, assuming it is made taking "enough care" (epistemological matters regarding computer-based simulations is a topic that deserve a number of works, from quite different perspectives; among other examples, [Tolk et al, 2013] and [Greca et al, 2014]). Moving first to "fully" continuous systems (even if limited to those modelled with ordinary differential equations, ODEs), we would like to remark that the probability of being able to integrate symbolically an ODE randomly generated is almost surely zero.…”

Section: Abstract: Dae Systems Initial Values Dynamic Model Superfmentioning

confidence: 99%

EUROSIM 2019 Abstract Volume

Gago¹,

Vasco²,

Łukawski³

et al. 2019

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ARGESIM is a non-profit scientific society generally aiming for dissemination of information on system simulation-from research via development to applications of system simulation. ARGESIM's primary publication is the journal SNE-Simulation Notes Europe with open access to all contributions; generally, the authors retain the copyright of their SNE contributions. This copyright regulation holds also for ARGESIM Reports and ARGESIM Advances in Simulation publishing conference volumes for ASIM, MTHMOD, and EUROSIM (in consideration of copyright regulations for related conference publications) and monographs on system simulation (mainly PhD theses). About ARGESIM ARGESIM is a non-profit society generally aiming for dissemination of information on system simulation from research via development to applications of system simulation. ARGESIM is closely cooperating with EU-ROSIM, the Federation of European Simulation Societies, and with ASIM, the German Simulation Society. ARGESIM is an 'outsourced' activity from the Mathematical Modelling and Simulation Group of TU Wien, there is also close cooperation with TU Wien (organisationally and personally). ARGESIM Publisher organizes publishing activities, with ISBN root 978-3-901608-xx-y and DOI root 10.11128/xx…x.

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Epistemology of modeling and simulation

Cited by 20 publications

References 38 publications

Hybrid Simulation: Historical lessons, present challenges and futures

Hybrid Simulation: Historical lessons, present challenges and futures

So You Think You Can Model? A Guide to Building and Evaluating Archaeological Simulation Models of Dispersals

EUROSIM 2019 Abstract Volume

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