We argue that abduction does not work in isolation from other inference mechanisms and illustrate this through an inference scheme designed to evaluate multiple hypotheses. We use game theory to relate the abductive system to actions that produce new information. To enable evaluation of the implications of this approach we have implemented the procedures used to calculate the impact of new information in a computer model. Experiments with this model display a number of features of collective belief-revision leading to consensus-formation, (...) such as the influence of bias and prejudice. The scheme of inferential calculations invokes a Peircian concept of ‘belief’ as the propensity to choose a particular course of action. (shrink)

We argue that abduction does not work in isolation from other inference mechanisms and illustrate this through an inference scheme designed to evaluate multiple hypotheses. We use game theory to relate the abductive system to actions that produce new information. To enable evaluation of the implications of this approach we have implemented the procedures used to calculate the impact of new information in a computer model. Experiments with this model display a number of features of collective belief-revision leading to consensus-formation, (...) such as the influence of bias and prejudice. The scheme of inferential calculations invokes a Peircian concept of ‘belief’ as the propensity to choose a particular course of action. (shrink)

Syntactic and structural models specify relationships between their constituents but cannot show what outcomes their interaction would produce over time in the world. Simulation consists in iterating the states of a model, so as to produce behaviour over a period of simulated time. Iteration enables us to trace the implications and outcomes of inference rules and other assumptions implemented in the models that make up a theory. We apply this method to experiments which we treat as models of the (...) particular aspects of reality they are designed to investigate. Scientific experiments are constantly designed and re-designed in the context of implementation and use. They mediate between theoretical understanding and the practicalities of engaging with the empirical and social world. In order to model experiments we need to identify and represent features that all experiments have in common. We treat these features as parameters of a general model of experiment so that by varying these parameters different types of experiment can be modelled. (shrink)

Reasons are given to justify the claim that computer simulations and computational science constitute a distinctively new set of scientific methods and that these methods introduce new issues in the philosophy of science. These issues are both epistemological and methodological in kind.

We simulate trial data to test speculative claims about research methods, such as the impact of publication bias.

A large number of engineering problems involve several conflicting objectives, which today are often solved through expensive simulation calculations. Methods based on meta-models are one of the approaches to solving this group of problems. In this paper, multiobjective optimization in the extraction system of a copper open-pit mine complex is presented by the modified-NBI optimization method and regression meta-model. For this purpose, two objective functions of maximizing the amount of total extraction, which is the sum of the extraction (...) of sulfide, oxide, low-grade ores, and waste in this mine, and minimizing the transport time of haulage according to the limitation of its storage capacity, transport equipment, and budget are considered. The Central Composite Design method is used to build the Design of Experiments for the design variables. The considered design variables are the number of trucks of 120 tons, 240 tons, 35 tons, and 100 tons. The number of targets considered in each design combination is considered the response surface. The suitable meta-model to maximize the total extraction rate and minimize the transport time of the haulage, two modified functions of nonlinear regression have been determined. The accuracy of the models for selection has been done using PRESS and R 2 statistics. The most common PRESS error has also been used to validate the meta-models. Then the multiobjective optimization problem was solved using the modified-NBI method. Finally, Pareto and optimal solutions using the proposed approach were presented and discussed. (shrink)

The paper deals with an intellectual and historical approach to the changing meanings of the term “model” in life sciences. The author 1st tries to understand how modeling has gradually spread over life sciences then he particularly focus on the birth of mathematical modeling in this field. This quite new practice offers new insights on the old debate concerning the mathematization of life sciences. Nowadays, through computers, mathematics not only analyze or quantify but model things: what does it mean? The (...) question turns out to be dramatic as far as digital simulation is concerned. That is the reason why he choosed to study a particular case: the history of the individual plant mathematical modeling. On this case, one may discern various epistemological standpoints that caused various reactions to the emergence of computer simulation, from the 50s to the 90s. The author shows that philosophical views often play a role in the history of sciences, especially in the choice of supposed proper mathematical formalisms. This will indicate that contemporary discourses tend to echo each other. That is the reason why he feels authorized to address the Foucault’s concept—épistémè—to denote these convergences between the scientific and the philosophical discourses. Finally, it is suggested that this épistémè gradually is changing because one can currently observe the emergence of a “graphical” thought through these simulation experiments, which tends to replace a more functionalist thought. (shrink)

Modeling and computer simulations, we claim, should be considered core philosophical methods. More precisely, we will defend two theses. First, philosophers should use simulations for many of the same reasons we currently use thought experiments. In fact, simulations are superior to thought experiments in achieving some philosophical goals. Second, devising and coding computational models instill good philosophical habits of mind. Throughout the paper, we respond to the often implicit objection that computer modeling is “not philosophical.”.

In recent years, a number of research projects have been proposed whose goal is to build large-scale simulations of brain mechanisms at unprecedented levels of biological accuracy. Here it is argued that the roles these simulations are expected to play in neuroscientific research go beyond the “synthetic method” extensively adopted in Artificial Intelligence and biorobotics. In addition we show that, over and above the common goal of simulating brain mechanisms, these projects pursue various modelling ambitions that can be sharply distinguished (...) from one another, and that correspond to conceptually different interpretations of the notion of “biological accuracy”. They include the ambition to reach extremely deep levels in the mechanistic decomposition hierarchy, to simulate networks composed of extremely large numbers of neural units, to build systems able to generate rich behavioural repertoires, to simulate “complex” neuron models, to implement the “best” theories available on brain structure and function. Some questions will be raised concerning the significance of each of these modelling ambitions with respect to the various roles played by simulations in the study of the brain. (shrink)

A method is presented for deciding whether correct predictions about other people are based on simulation or theory use. The differentiating power of this method was assessed with cognitive estimation biases (e.g. estimating the area of Brazil) in two variations. Experiments 1 and 2 operated with the influence of response scales of different length. Experiment 3 used the difference between free estimates that tended to be far off the true value and estimates constrained by an appropriate response scale, where (...) estimates became greatly more realistic. The critical question is how well observer subjects can predict these target biases under two different presentation conditions. Response scale biases (Experiments 1 and 2) were more strongly predicted when observer subjects were presented with the two scales juxtaposed, than when responses for each scale were given independently. This speaks for the use of a theory, since simulation should, if there is any difference at all, be made more difficult by the juxtaposition of conditions. The difference between free and constrained estimations (Experiment 3) was more strongly predicted under independent than under juxtaposed presentation. This speaks for the use of simulation since use of a theory should, if anything, be helped by juxtaposition of problems since it helps highlight the theoretically relevant factor. Results are discussed in view of recent proposals about when simulation is likely to be used, i.e. for belief fixation but not action prediction (Stich and Nichols, 1995b), for content fixation (Heal, 1996a), and for rational effects only (Heal, 1996b). (shrink)

There is much disagreement about how extensive a role theoretical mind-reading, behavior-reading, and simulation each have and need to have in our knowing and understanding other minds, and how each method is implemented in the brain, but less discussion of the epistemological question what it is about the products of these methods that makes them count as knowledge or understanding. This question has become especially salient recently as some have the intuition that mirror neurons can bring understanding of (...) another's action despite involving no higher-order processing, whereas most epistemologists writing about understanding think that it requires reflective access to one's grounds, which is closer to the intuitions of other commenters on mirror neurons. I offer a definition of what it is that makes something understanding that is compelling independently of the context of cognition of other minds, and use it to show two things: 1) that theoretical mind-reading and simulation bring understanding in virtue of the same epistemic feature, and 2) why the kind of motor representation without propositional attitudes that is done by mirror neurons is sufficient for action understanding. I further suggest that more attention should be paid to the potential disadvantages of a simulative method of knowing. Though it can be more efficient in some cases, it can also bring vulnerability, wear and tear on one's personal equipment, and unintended mimicry. (shrink)

With the mutual exchange and integration of world football, modern football is in an increasingly comprehensive direction. This research mainly discusses complexity computer simulation in the study of the overall play of campus football. Complexity computer simulation is used to design the background of the simulated football field, and the area is divided according to the size ratio of the actual football field. Then, it uses drawing software to draw the football and player controls. The construction of the (...) knowledge base of this paper is mainly combined with the functional modules of rapid formation and response tactics. In the fast formation function, the required formation can be quickly given through football experience and knowledge rules. In the applied tactics function, for the responsibilities of forwards, midfielders, defenders, and other roles, the tactics implemented are given, including partially coordinated offensive and defensive tactics, personal offensive and defensive tactics, and set-ball tactics. The “holistic play” football tactics studied in this paper use XML files as recording and playback data, which not only greatly reduce the amount of file data but also make the operation of XML files intuitive and simple. XML can not only realize the recording and playback of player and football track but also be used in the function of rapid formation. The coach uses the “holistic play” football tactics simulation to demonstrate the movement route through the image, guide the players in each position to perceive the game scene by observing the movement route, and analyze and judge the tactical coordination of their respective positions. The computer simulation tactical analysis of the precision of the passing and running and the path coefficient of the passing factor is 0.606 and 0.59, respectively. This research helps to provide guidance on the overall playing tactics of football. (shrink)

With the rapid development of sensor technology for automated driving applications, the fusion, analysis, and application of multimodal data have become the main focus of different scenarios, especially in the development of mobile edge computing technology that provides more efficient algorithms for realizing the various application scenarios. In the present paper, the vehicle status and operation data were acquired by vehicle-borne and roadside units of electronic registration identification of motor vehicles. In addition, a motion model and an identification system for (...) the single-vehicle lane-change process were established by mobile edge computing and self-organizing feature mapping. Two scenarios were modeled and tested: lane change with no vehicles in the target lane and lane change with vehicles in the target lane. It was found that the proposed method successfully identified the stochastic parameters in the process of driving trajectory simulation, and the standard deviation between simulation and the measured results obeyed a normal distribution. The proposed methods can provide significant practical information for improving the data processing efficiency in automated driving applications, for solving single-vehicle lane-change applications, and for promoting the formation of a closed loop from sensing to service. (shrink)

Computer simulations have conventionally been understood to be either extensions of formal methods such as mathematical models or as special cases of empirical practices such as experiments. Here, I argue that computer simulations are best understood as instruments. Understanding them as such can better elucidate their actual role as well as their potential epistemic standing in relation to science and other scientific methods, practices and devices.

This article proposes an Analytic Hierarchy Process Dempster-Shafer and similarity-based network selection algorithm for the scenario of dynamic changes in user requirements and network environment; combines machine learning with network selection and proposes a decision tree-based network selection algorithm; combines multiattribute decision-making and genetic algorithm to propose a weighted Gray Relation Analysis and genetic algorithm-based network access decision algorithm. Firstly, the training data is obtained from the collaborative algorithm, and it is used as the training set, and the network attributes (...) are used as the attribute set, and the continuous attributes are discretized by dichotomization, and the attribute that can make the greatest information gain is selected as the division feature, and a decision tree with strong generalization ability is finally obtained, which is used as the decision basis for network access selection. The simulation results show that the algorithm proposed in this thesis can effectively improve user service quality under three services, and the algorithm is simple and effective with low complexity. It first uses AHP-DS hierarchical analysis to establish a recursive hierarchy for the network selection problem and obtains the subjective weights of network attributes through the judgment matrix. Then, it uses a genetic algorithm to adjust the subjective weight, defines the fitness function in the genetic algorithm-based on gray correlation analysis, adjusts the weights of the selection operator, crossover operator, and variation operator in the genetic algorithm, and gets the network with the largest fitness as the target network, which can effectively improve the user service quality. (shrink)

This unique volume introduces and discusses the methods of validating computer simulations in scientific research. The core concepts, strategies, and techniques of validation are explained by an international team of pre-eminent authorities, drawing on expertise from various fields ranging from engineering and the physical sciences to the social sciences and history. The work also offers new and original philosophical perspectives on the validation of simulations. Topics and features: introduces the fundamental concepts and principles related to the validation of computer (...) simulations, and examines philosophical frameworks for thinking about validation; provides an overview of the various strategies and techniques available for validating simulations, as well as the preparatory steps that have to be taken prior to validation; describes commonly used reference points and mathematical frameworks applicable to simulation validation; reviews the legal prescriptions, and the administrative and procedural activities related to simulation validation; presents examples of best practice that demonstrate how methods of validation are applied in various disciplines and with different types of simulation models; covers important practical challenges faced by simulation scientists when applying validation methods and techniques; offers a selection of general philosophical reflections that explore the significance of validation from a broader perspective. This truly interdisciplinary handbook will appeal to a broad audience, from professional scientists spanning all natural and social sciences, to young scholars new to research with computer simulations. Philosophers of science, and methodologists seeking to increase their understanding of simulation validation, will also find much to benefit from in the text. (shrink)

A new proof is given of the celebrated theorem of M. Davis, H. Putnam and J. Robinson concerning exponential Diophantine representation of recursively enumerable predicates. The proof goes by induction on the defining scheme of a partial recursive function.

This research investigated how dramatization simulation affected nursing students' ethical attitudes. Most nurses and nursing students encounter ethical issues in their healthcare practices. Students who receive an education in ethics are better equipped to solve ethical problems, develop ethical sensitivity, and adopt an ethical attitude. Dramatization simulation, which has recently been applied in nursing education, is said to be an effective teaching method. A mixed-method approach was employed in the research. The sample consisted of 60 students enrolled in (...) the final year of the Nursing Department of the Faculty of Health Sciences at a State university. Students were randomly assigned to experimental and control groups. In the experimental group, the dramatization simulation method was used to evaluate the effectiveness of the training method. The data were collected using the Descriptive Characteristics Form, Ethical Principles Attitude Scale, and Semi-Structured Focus Group Interview Form. SPSS 22 software was used to analyze the quantitative data, and Colaizzi's phenomenological analysis and MAXQDA 2020 software were used to analyze the qualitative data. The post-test total score of the group ethical attitude scale for the students in the experimental group showed a statistically significant improvement (p < 0.05). Additionally, the students in the experimental group's post-test Ethical Attitude Scale total score outperformed those in the control group statistically significantly (p < 0.05). The following themes were found: (1) perspectives on dramatization simulation and (2) perspectives on ethical attitude. To help nursing students develop ethical attitudes, we recommend using dramatization simulation as a teaching method. In addition, we recommend that this study be conducted in larger sample groups and on different topics. The recommendations were explored in more detail in the article. (shrink)

In this paper, we present an intensive investigation of the finite volume method compared to the finite difference methods. In order to show the main difference in the way of approaching the solution, we take the Burgers equation and the Buckley–Leverett equation as examples to simulate the previously mentioned methods. On the one hand, we simulate the results of the finite difference methods using the schemes of Lax–Friedrichs and Lax–Wendroff. On the other hand, we apply Godunov’s scheme (...) to simulate the results of the finite volume method. Moreover, we show how starting with a variational formulation of the problem, the finite element technique provides piecewise formulations of functions defined by a collection of grid data points, while the finite difference technique begins with a differential formulation of the problem and continues to discretize the derivatives. Finally, some graphical and numerical comparisons are provided to illustrate and corroborate the differences between these two main methods. (shrink)

Bayesian epistemologyEpistemology 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 updatingUpdating emerge as constraints on the formation of rational belief. Bayesian epistemologyEpistemology has led to useful explications of notions such asConfirmation confirmation. It thus is natural to ask whether Bayesian epistemologyEpistemology 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 epistemologyEpistemology is briefly summarized and then applied to validation. UpdatingUpdating is shown to form a viable method for data-driven validation. Bayesians can also express how a simulation obtains prior credibilityCredibility because the underlying conceptual modelConceptual model is credible. But the impact of this prior credibilityCredibility is indirect since simulations at best provide partial and approximate solutions to theConceptual model 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 epistemologyEpistemology in validation, e.g., by comparing it to a falsificationist approach. It is argued that Bayesian epistemologyEpistemology goes beyond mere calibrationCalibration and that it can provide the foundations for a sound evaluationEvaluation of computer simulations. (shrink)

If the twentieth century was the age of the world picture taken as a photograph of the Whole Earth from outer space, today’s observations of the planet are produced by means of computer simulation. Pandemic models are of paramount sociological interest in this respect, since modelling contagion is closely intertwined with modelling the material connectivities of social life. By envisioning the global dynamics of disease transmission, pandemic simulations enact the relationscapes of a transnational world. This article seeks to analyse (...) such an enactment: It asks how simulation methods can establish a particular relation to the social from within the social. To provide an answer to this question, and adopting Niklas Luhmann’s theory of world society, pandemic simulations are described as modes of global self-observation that can be specified factually, socially, spatially and temporally. They instantiate a ‘doubling of reality’ designed to apprehend the potential future threat of disease transmission along the pathways marked by global infrastructures. They constitute scopic regimes that virtually synthesize a global situation of universal communicability in order to turn the world into an object of political intervention. (shrink)

The importation of computational methods into biology is generating novel methodological strategies for managing complexity which philosophers are only just starting to explore and elaborate. This paper aims to enrich our understanding of methodology in integrative systems biology, which is developing novel epistemic and cognitive strategies for managing complex problem-solving tasks. We illustrate this through developing a case study of a bimodal researcher from our ethnographic investigation of two systems biology research labs. The researcher constructed models of metabolic and (...) cell-signaling pathways by conducting her own wet-lab experimentation while building simulation models. We show how this coupling of experiment and simulation enabled her to build and validate her models and also triangulate and localize errors and uncertainties in them. This method can be contrasted with the unimodal modeling strategy in systems biology which relies more on mathematical or algorithmic methods to reduce complexity. We discuss the relative affordances and limitations of these strategies, which represent distinct opinions in the field about how to handle the investigation of complex biological systems. (shrink)

(This is for the Cambridge Handbook of Analytic Philosophy, edited by Marcus Rossberg) In this handbook entry, I survey the different ways in which formal mathematical methods have been applied to philosophical questions throughout the history of analytic philosophy. I consider: formalization in symbolic logic, with examples such as Aquinas’ third way and Anselm’s ontological argument; Bayesian confirmation theory, with examples such as the fine-tuning argument for God and the paradox of the ravens; foundations of mathematics, with examples such (...) as Hilbert’s programme and Gödel’s incompleteness theorems; social choice theory, with examples such as Condorcet’s paradox and Arrow’s theorem; ‘how possibly’ results, with examples such as Condorcet’s jury theorem and recent work on intersectionality theory; and the application of advanced mathematics in philosophy, with examples such as accuracy-first epistemology. (shrink)

In this volume, scientists, historians, and philosophers join to examine computer simulations in scientific practice. One central aim of the volume is to provide a multiperspective view on the topic. Therefore, the text includes philosophical studies on computer simulations, as well as case studies from simulation practice, and historical studies of the evolution of simulations as a research method.

This article provides a survey of some of the reasons why computational approaches have become a permanent addition to the set of scientific methods. The reasons for this require us to represent the relation between theories and their applications in a different way than do the traditional logical accounts extant in the philosophical literature. A working definition of computer simulations is provided and some properties of simulations are explored by considering an example from quantum chemistry.

In the 1990s, Building Information Modeling (BIM) software significantly altered architectural approaches to planning and building. Based on parametric methods, BIM technologies sought to simulate the construction process prior to a building’s realisation. These computer simulations challenged the existing practice of representing a building through plan, section and elevation, proposing that one computational model could create a more efficient way of building. The history of BIM explorations and applications, while hardly linear, can be traced back to developments in computing (...) since the post-war period. This article maps some of these histories by examining how the computational model became an organisational infrastructure, collecting data about design and building parameters, and facilitating knowledge transfer across industries. Special attention will be given to the foundational role of Charles Eastman’s work on a Building Description System (BDS) in the 1970s, as well as Robert Aish’s contribution to RUCAPS, one of the earliest applications of Building Modeling for the design of parametric structures. I will further address research on interface technologies and computational curve modelling as well as the popularisation of Building Information systems through the office of Gehry Partners. By highlighting the interrelated nature of technology and cultural shifts in the making of BIM, this contribution sheds light on the epistemic status of computer simulations in architecture, and the dynamics of the design and building processes in which they are used. (shrink)

In the 1990s, Building Information Modeling (BIM) software significantly altered architectural approaches to planning and building. Based on parametric methods, BIM technologies sought to simulate the construction process prior to a building’s realisation. These computer simulations challenged the existing practice of representing a building through plan, section and elevation, proposing that one computational model could create a more efficient way of building. The history of BIM explorations and applications, while hardly linear, can be traced back to developments in computing (...) since the post-war period. This article maps some of these histories by examining how the computational model became an organisational infrastructure, collecting data about design and building parameters, and facilitating knowledge transfer across industries. Special attention will be given to the foundational role of Charles Eastman’s work on a Building Description System (BDS) in the 1970s, as well as Robert Aish’s contribution to RUCAPS, one of the earliest applications of Building Modeling for the design of parametric structures. I will further address research on interface technologies and computational curve modelling as well as the popularisation of Building Information systems through the office of Gehry Partners. By highlighting the interrelated nature of technology and cultural shifts in the making of BIM, this contribution sheds light on the epistemic status of computer simulations in architecture, and the dynamics of the design and building processes in which they are used. (shrink)

In 1904, Norwegian physicist Vilhelm Bjerknes published what would become a landmark paper in the history of meteorology. In that paper, he proposed that daily weather forecasts could be made by calculating later states of the atmosphere from an earlier state using the laws of hydrodynamics and thermodynamics (Bjerknes 1904). He outlined a set of differential equations to be solved and advocated the development of graphical and numerical solution methods, since analytic solution was out of the question. Using these (...) theory-based equations to produce daily forecasts, however, turned out to be more difficult than anticipated. Graphical solution techniques had limited success, and a first attempt to use .. (shrink)

Proposed models of closed timelike curves have been shown to enable powerful information-processing protocols. We examine the simulation of models of CTCs both by other models of CTCs and by physical systems without access to CTCs. We prove that the recently proposed transition probability CTCs are physically equivalent to postselection CTCs, in the sense that one model can simulate the other with reasonable overhead. As a consequence, their information-processing capabilities are equivalent. We also describe a method for quantum computers (...) to simulate Deutschian CTCs. In cases for which the overhead is reasonable, it might be possible to perform the simulation in a table-top experiment. This approach has the benefit of resolving some ambiguities associated with the equivalent circuit model of Ralph et al. Furthermore, we provide an explicit form for the state of the CTC system such that it is a maximum-entropy state, as prescribed by Deutsch. (shrink)

Theories of mind draw on processes that represent mental states and their computational connections; simulation, in addition, draws on processes that replicate (Heal 1986 ) a sequence of mental states. Moreover, mental simulation can be triggered by input from imagination instead of real perceptions. To avoid confusion between mental states concerning reality and those created in simulation, imagined contents must be quarantined. Goldman bypasses this problem by giving pretend states a special role to play in simulation (...) (Goldman 2006 ). We argue that this path leads to the resurgence of the threat of collapse (Davies 1994 ), diluting the principled distinction between simulation and theory use. Exploration of a related method of real-mental states operating in a pretend mode leads to a factually untenable model. Our main goal here is to raise this problem as a challenge for Goldman’s reconfigured simulation theory. Only at the end we will briefly sketch a possible alternative way of quarantine that preserves the replicative element of simulation and avoids collapse. Figure 1 provides a guide to our argument. (shrink)

This uniquely inspirational and practical book explores human simulation, which is the application of computational modeling and simulation to research subjects in the humanities disciplines. It delves into the fascinating process of collaboration among experts who usually don’t have much to do with one another – computer engineers and humanities scholars – from the perspective of the humanities scholars. It also explains the process of developing models and simulations in these interdisciplinary teams. Each chapter takes the reader on (...) a journey, presenting a specific theory about the human condition, a model of that theory, discussion of its implementation, analysis of its results, and an account of the collaborative experience. Contributing authors with different fields of expertise share how each model was validated, discuss relevant datasets, explain development strategies, and frankly discuss the ups and downs of the process of collaborative development. Readers are given access to the models and will also gain new perspectives from the authors’ findings, experiences, and recommendations. Today we are in the early phases of an information revolution, combining access to vast computing resources, large amounts of human data through social media, and an unprecedented richness of methods and tools to capture, analyze, explore, and test hypotheses and theories of all kinds. Thus, this book’s insights will be valuable not only to students and scholars of humanities subjects, but also to the general reader and researchers from other disciplines who are intrigued by the expansion of the information revolution all the way into the humanities departments of modern universities. (shrink)

The central claim of this paper is that computer simulation provides (though not exclusively) a qualitatively new and different methodology for the physical sciences, and that this methodology lies somewhere intermediate between traditional theoretical physical science and its empirical methods of experimentation and observation. In many cases it involves a new syntax which gradually replaces the old, and it involves theoretical model experimentation in a qualitatively new and interesting way. Scientific activity has thus reached a new milestone somewhat (...) comparable to the milestones that started the empirical approach (Galileo) and the deterministic mathematical approach to dynamics (the old syntax of Newton and Laplace). Computer simulation is consequently of considerable philosophical interest. In view of further technical developments in the near future, computer experts suggest that we are at present only at the very beginning of this new era. (shrink)

The systemic complexity of sustainable development imposes a major cognitive challenge to students’ learning. Faculty can explore new approaches in the classroom to teach the topic successfully, including the use of technology. We conducted an experiment to compare the effectiveness of a simulation vis-à-vis a case-based method to teach sustainable development. We found that both pedagogical methods are effective for teaching this concept, although our results support the idea that simulations are slightly more effective than case studies, particularly (...) to teach its multidimensional and inter-temporal nature. Therefore, our findings suggest the use of both simulations and case studies as pedagogical tools to convey the main ideas associated with sustainable development. (shrink)

The present paper intends to show that computer simulations used in science are akin to fiction. Starting from the problem of defining computer simulation, the paper discusses the uses and disadvantages of simulations in science. Computer simulations have a representational function, but they do not resemble the phenomena that they purport to represent. Computer simulations do not preserve the content of the models, input data, and theories from which they proceed, since the content is modified by computational processes. Because (...) of the complexities of these processes, we cannot control or test the methods used to process the content of computer simulations. Still, simulations may help to explain the behaviour of a possible aspect of the phenomenon under examination. Although their role in doing so may be limited, by conforming to and immersing us in the worldview of science, simulations, thus reinforce the intuitions of the existing body of scientific knowledge, and similarly to the “believable fiction” described by John Woods, provide genuine understanding. (shrink)

The procedures of validating computer simulations of particle physicsParticle physics events at the LHCLarge Hadron Collider are summarized. Because of the strongly fluctuating particle content of LHC events and detectorDetector interactions, particle-based Monte Carlo methods are an indispensable tool for dataData analysis analysis. Simulation in particle physicsParticle physics is founded on factorizationFactorization and thus its global validation can be realized by validating each individual step in the simulation. This can be accomplished by drawing on results of previousMeasurement (...) measurements, in situ studies, and models. What is particularly important in particle physicsParticle physics is to quantify how well a simulation is validated such that a systematic uncertainty can be assigned to a measurement. The simulation is tested for a wide range of processes and agrees with dataData within the assigned uncertainties. (shrink)

The extended system method of Nosé and Hoover for the control of temperature of a classical ensemble if applied to the de Broglie-Bohm-Vigier formulation of quantum mechanics. This allows for the simulation of the motion of a quantum particle at a constant preset temperature. A specific algorithm for numerical solution of the resulting equations of motion, based on the application of the methods of molecular dynamics simulation, is provided.

Computer simulations are widely used for surrogative reasoning in scientific research. They also play a crucial role in engineering, more specifically in the design of new robotic systems, yet the nature of this role has been little discussed so far in the philosophy of technology literature. The main claim made in this article is that the notion of surrogative reasoning is central to understanding how computer simulations can serve the purpose of designing new robots. More specifically, it is argued that (...) computer simulations can support two forms of surrogative reasoning, which are called model-oriented and prediction-oriented, whose inferential structure is reconstructed to some extent. And it is argued that, when computer simulations are used to design new robots, they are distinctively used in the model-oriented way. By unravelling the structure of the computer simulation-supported methods adopted in robotic design, this article may contribute to a finer-grained understanding of the epistemic processes involved in technological research. (shrink)