1,721,175 research outputs found
Should Validation and Verification Be Separated Strictly?
No full textVerification and validation are methods with which computer simulations are tested. While many practitioners draw a clear line between verification and validation and demand that the former precedes the latter, some philosophers have suggested that the distinction has been over-exaggerated. This chapter clarifies the relationship between verification and validation. Regarding the latter, validation of the conceptual and of the computational model are distinguished. I argue that, as a method, verification is clearly different from validation of either of the models. However, the methods are related to each other as follows: If we allow that the validation of the computational model need not include the comparison between simulation output and measured data, then the computational model may be validated by validating the conceptual model independently and by verifying the simulation with respect to it. This is often not realistic, however, because, in most cases, the conceptual model cannot be validated independently from the simulation. In such cases, the computational model is verified with the aim to use it as an appropriate substitute for the conceptual model. Then simulation output is compared to measured data to validate both the computational and the conceptual model. I analyze the underlying inferences and argue that they require some prior confidence (i) in the conceptual model and (ii) in verification. This suggests that verification precede validation that proceeds via a comparison between simulation output and measured data. Recent arguments to the effect that the distinction between verification and validation is not clear-cut do not refute these results, or so I argue against philosopher E. Winsberg
Simulation Validation from a Bayesian Perspective
No full textBayesian epistemology offers a powerful framework for characterizing scientific inference. Its basic idea is that rational belief comes in degrees that can be measured in terms of probabilities. The axioms of the probability calculus and a rule for updating (e.g., Bayesian conditionalization) emerge as constraints on the formation of rational belief. Bayesian epistemology has led to useful explications of notions such as confirmation. It thus is natural to ask whether Bayesian epistemology offers a useful framework for thinking about the inferences implicit in the validation of computer simulations. The aim of this chapter is to answer this question. Bayesian epistemology is briefly summarized and then applied to validation. Updating is shown to form a viable method for data-driven validation. Bayesians can also express how a simulation obtains prior credibility because the underlying conceptual model is credible. But the impact of this prior credibility is indirect since simulations at best provide partial and approximate solutions to the conceptual model. Fortunately, this gap between the simulations and the conceptual model can be addressed using what we call Bayesian verification. The final part of the chapter systematically evaluates the use of Bayesian epistemology in validation, e.g., by comparing it to a falsificationist approach. It is argued that Bayesian epistemology goes beyond mere calibration and that it can provide the foundations for a sound evaluation of computer simulations
What is a Computer Simulation and What does this Mean for Simulation Validation?
No full textMany questions about the fundamentals of some area take the form “What is ...?” It does not come as a surprise then that, at the dawn of Western philosophy, Socrates asked the questions of what piety, courage, and justice are. Nor is it a wonder that the philosophical preoccupation with computer simulations centered, among other things, about the question of what computer simulations are. Very often, this question has been answered by stating that computer simulation is a species of a well-known method, e.g., experimentation. Other answers claim at least a close relationship between computer simulation and another method. In any case, correct answers to the question of what a computer simulation is should help us to better understand what validation of simulations is. The aim of this chapter is to discuss the most important proposals to understand computer simulation in terms of another method and to trace consequences for validation. Although it has sometimes been claimed that computer simulations are experiments, there are strong reasons to reject this view. A more appropriate proposal is to say that computer simulations often model experiments. This implies that the simulation scientists should to some extent imitate the validation of an experiment. But the validation of computer simulations turns out to be more comprehensive. Computer simulations have also been conceptualized as thought experiments or close cousins of the latter. This seems true, but not very telling since thought experiments are not a standard method and since it is controversial how they contribute to our acquisition of knowledge. I thus consider a specific view on thought experiments to make some progress on understanding simulations and their validation. There is finally a close connection between computer simulation and modeling, and it can be shown that the validation of a computer simulation is the validation of a specific model, which may either be thought to be mathematical or fictional
What is Validation of Computer Simulations? Toward a Clarification of the Concept of Validation and of Related Notions
No full textThis chapter clarifies the concept of validation of computer simulations by comparing various definitions that have been proposed for the notion. While the definitions agree in taking validation to be an evaluation, they differ on the following questions: 1. What exactly is evaluated – results from a computer simulation, a model, a computer code? 2. What are the standards of evaluation – truth, accuracy and credibility or also something else? 3. What type of verdict does validation lead to – that the simulation is such and such good, or that it passes a test defined by a pre-defined threshold? 4. How strong needs the case to be for the verdict? 5. Does validation necessarily proceed by comparing simulation outputs with measured data? Along with the questions, the chapter explains notions that figure prominently in them, e.g. the concepts of accuracy and credibility. It further discusses natural answers to the questions as well as arguments that speak in favor and against these answers. The aim is to obtain a better understanding of the options we have for defining validation and how they are related to each other
Was ist eine Computersimulation?
No full textOb es um Quarks, Biomoleküle oder Supernovae geht – bei ihren Untersuchungen stützt sich die heutige Physik oft auf die Computersimulation. Anfängliches Unbehagen über die Methode oder der flaue Gag, damit werde wissenschaftliches Vorgehen bloß simuliert, sind längst passé. Doch welchen Beitrag leistet die Methode zur physikalischen Forschung und wie sind ihre Ergebnisse zu bewerten
Karl Raimund Popper: Science: Conjectures and Refutations. Wissenschaft: Vermutungen und Widerlegungen
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