A central goal of contemporary cognitive science is the explanation of cognitive abilities or capacities. [Cummins 1983] During the last three decades a wide range of cognitive capacities have been subjected to careful empirical scrutiny. The adult's ability to produce and comprehend natural language sentences and the child's capacity to acquire a natural language were among the first to be explored. [Chomsky 1965, Fodor, Bever & Garrett 1974, Pinker 1989] There is also a rich literature on the ability to solve (...) mathematical problems [Greeno 1983], the ability to recognize objects visually [Rock 1983, Gregory 1970, Marr 1982], the ability to manipulate and predict the behavior of middle sized physical objects [McClosky 1983, Hayes 1985], and a host of others. (shrink)

Recently, there has been a resurgence of interest in theories of mindreading. New discoveries in neuroscience have revitalized the languishing debate. The discovery of so-called mirror neurons has revived interest particularly in the Simulation Theory (ST) of mindreading. Both ST proponents and theorists studying mirror neurons have argued that mirror neurons are strong evidence in favor of ST over Theory Theory (TT). In this paper I argue against the prevailing view that mirror neurons are evidence for the ST of (...) mindreading. My view is that on an appropriate construal of their function, mirror neurons do not operate like simulation theorists claim. In fact, mirror neurons are more appropriately understood as one element in an information-rich mindreading process. As such, mirror neurons fit in better with some sort of TT account of mindreading. I offer a positive account, the Model TT, which better explains the role of mirror neurons in social cognition. (shrink)

Until recently, philosophers debating the rationality of time-biases have supposed that people exhibit a first-person hedonic bias toward the future, but that their non-hedonic and third-person preferences are time-neutral. Recent empirical work, however, suggests that our preferences are more nuanced. First, there is evidence that our third-person preferences exhibit time-neutrality only when the individual with respect to whom we have preferences—the preference target—is a random stranger about whom we know nothing; given access to some information about the preference target, third-person (...) preferences mirror first-person preferences. As a result, the simulation hypothesis has been proposed, according to which third-person preferences will mirror first-person preferences when we can simulate the mental states of the preference target. Second, there is evidence that we prefer negative hedonic events to be in our past (we are first-person negatively hedonically future-biased) only when we view future events as fixed and in no way under our control. By contrast, when we perceive it to be within our power to mitigate the badness of future events, we are first-person negatively hedonically past-biased. This is the mitigation hypothesis. We distinguish two versions of the mitigation hypothesis, the squirrelling version and the heuristic version. We ran a study which tested the simulation hypothesis, and which aimed to determine whether the squirrelling or the heuristic version of the mitigation hypothesis enjoys more empirical support. We found support for the heuristic version of the hypothesis, but no support for the squirrelling version. (shrink)

Imitation, deliberation, and mindreading are characteristically human sociocognitive skills. Research on imitation and its role in social cognition is flourishing across various disciplines. Imitation is surveyed in this target article under headings of behavior, subpersonal mechanisms, and functions of imitation. A model is then advanced within which many of the developments surveyed can be located and explained. The shared circuits model (SCM) explains how imitation, deliberation, and mindreading can be enabled by subpersonal mechanisms of control, mirroring, and simulation. It (...) is cast at a middle, functional level of description, that is, between the level of neural implementation and the level of conscious perceptions and intentional actions. The SCM connects shared informational dynamics for perception and action with shared informational dynamics for self and other, while also showing how the action/perception, self/other, and actual/possible distinctions can be overlaid on these shared informational dynamics. It avoids the common conception of perception and action as separate and peripheral to central cognition. Rather, it contributes to the situated cognition movement by showing how mechanisms for perceiving action can be built on those for active perception.;>;>The SCM is developed heuristically, in five layers that can be combined in various ways to frame specific ontogenetic or phylogenetic hypotheses. The starting point is dynamic online motor control, whereby an organism is closely attuned to its embedding environment through sensorimotor feedback. Onto this are layered functions of prediction and simulation of feedback, mirroring, simulation of mirroring, monitored inhibition of motor output, and monitored simulation of input. Finally, monitored simulation of input specifying possible actions plus inhibited mirroring of such possible actions can generate information about the possible as opposed to actual instrumental actions of others, and the possible causes and effects of such possible actions, thereby enabling strategic social deliberation. Multiple instances of such shared circuits structures could be linked into a network permitting decomposition and recombination of elements, enabling flexible control, imitative learning, understanding of other agents, and instrumental and strategic deliberation. While more advanced forms of social cognition, which require tracking multiple others and their multiple possible actions, may depend on interpretative theorizing or language, the SCM shows how layered mechanisms of control, mirroring, and simulation can enable distinctively human cognitive capacities for imitation, deliberation, and mindreading. (shrink)

In this paper, I propose that, in addition to the multiverse hypothesis, which is commonly taken to be an alternative explanation for fine-tuning, other than the design hypothesis, the simulation hypothesis is another explanation for fine-tuning. I then argue that the simulation hypothesis undercuts the alleged evidential connection between ‘designer’ and ‘supernatural designer of immense power and knowledge’ in much the same way that the multiverse hypothesis undercuts the alleged evidential connection between ‘fine-tuning’ and ‘fine-tuner’ (or ‘designer’). If (...) this is correct, then the fine-tuning argument is a weak argument for the existence of God. (shrink)

It is generally assumed that the debate between theory‐theory and simulation theory is an empirical one, but this view of the structure of the debate is misleading. It is an a priori truth that theory‐theory is mistaken and equally a priori that simulation in one sense (here labelled ‘co‐cognition’) is central in thinking about the thoughts of others. Given this, it is a further question how our co‐cognitive powers are realized in sub‐personal machinery. Here simulation in quite (...) another sense (that involving such ideas as ‘pretend states’ and ‘off‐line’ mental processes) may provide one possible answer. (shrink)

This paper proposes a brain-inspired cognitive architecture that incorporates approximations to the concepts of consciousness, imagination, and emotion. To emulate the empirically established cognitive efficacy of conscious as opposed to non-conscious information processing in the mammalian brain, the architecture adopts a model of information flow from global workspace theory. Cognitive functions such as anticipation and planning are realised through internal simulation of interaction with the environment. Action selection, in both actual and internally simulated interaction with the environment, is mediated (...) by affect. An implementation of the architecture is described which is based on weightless neurons and is used to control a simulated robot. (shrink)

Simulation modeling, the core thesis of Calculated Surprises, is transforming the established conception of mathematical modeling in fundamental ways. These transformations feed back into philosophy of science, opening up new perspectives on longstanding oppositions. The book integrates historical features with both practical case studies and broad reflections on science and technology.

According to the most common interpretation of the simulation argument, we are very likely to live in an ancestor simulation. It is interesting to ask if some families of simulations are more likely than others inside the space of all simulations. We argue that a natural probability measure is given by computational complexity: easier simulations are more likely to be run. Remarkably this allows us to extract experimental predictions from the fact that we live in a simulation. (...) For instance we show that it is very likely that humanity will not achieve interstellar travel and that humanity will not meet other intelligent species in the universe, in turn explaining the Fermi's Paradox. On the opposite side, experimental falsification of any of these predictions would constitute evidence against our reality being a simulation. (shrink)

Previous studies have shown that object properties are processed faster when they follow properties from the same perceptual modality than properties from different modalities. These findings suggest that language activates sensorimotor processes, which, according to those studies, can only be explained by a modal account of cognition. The current paper shows how a statistical linguistic approach of word co-occurrences can also reliably predict the category of perceptual modality a word belongs to (auditory, olfactory–gustatory, visual–haptic), even though the statistical linguistic approach (...) is less precise than the modal approach (auditory, gustatory, haptic, olfactory, visual). Moreover, the statistical linguistic approach is compared with the modal embodied approach in an experiment in which participants verify properties that share or shift modalities. Response times suggest that fast responses can best be explained by the linguistic account, whereas slower responses can best be explained by the embodied account. These results provide further evidence for the theory that conceptual processing is both linguistic and embodied, whereby less precise linguistic processes precede precise simulation processes. (shrink)

Heal (1996a) maintains that evidence of cognitive penetrability doesn't determine whether stimulation theory or theory theory wins. Given the wide variety of mechanisms and processes that get called ‘simulation’, we argue that it's not useful to ask‘who wins?’. The label ‘simulation’picks out no natural or theoretically interesting category. We propose a more fine‐grained taxonomy and argue that some processes that have been labelled ‘simulation’, eg.,‘actual‐situation‐simulation’, clearly do exist, while other processes labelled ‘simulation’, e.g., ‘pretence‐driven‐off‐line‐simulation’are (...) quite controversial. We do concede that evidence of cognitive penetrability isn't decisive evidence against pretence‐driven‐off‐line‐simulation. Nonetheless, advocates of pretence‐driven‐off‐line‐simulation need to provide some explanation of the experimental evidence of penetrability. We argue that Heal's suggestion that simulation is restricted to‘rational’processes is unprincipled, and we offer an alternative proposal for restricted simulation. (shrink)

Mental or computer simulation of cause and effect of certain behaviors is a recognized approach to changing one’s attitude or triggering an action. Meanwhile, psychology research results suggest that frequency of simulation may affect the corresponding persuasiveness. This paper argues that with always-on sensing and data-driven visualization technologies, interactive tangible systems can be designed to simulate hypothetical outcomes of real-life behaviors in everyday contexts, which repeatedly stimulate users’ imagination of behavioral consequences and thereby behavioral intentions. To investigate the (...) effect, a working prototype of Incingarette, including a smart ashtray in connection with a digital picture frame, was built. When the ashtray is used for smoking, the digital picture is incrementally covered by virtual dust. Field trials involved participants in five daily smoking sessions. Post-session surveys show increasingly stronger perceived causality between smoking and the simulated outcomes, increasingly more vivid mental imagery of consequences, and increasingly intense intention to reduce smoking. Results suggest that repeatedly presenting simulated outcomes cognitively linked to real-life behaviors can increase behavioral intentions. (shrink)

I argue that at least one of the following propositions is true: the human species is very likely to become extinct before reaching a ’posthuman’ stage; any posthuman civilization is extremely unlikely to run a significant number of simulations of its evolutionary history ; we are almost certainly living in a computer simulation. It follows that the belief that there is a significant chance that we shall one day become posthumans who run ancestor-simulations is false, unless we are currently (...) living in a simulation. I discuss some consequences of this result. (shrink)

“The Matrix is a computer-generated dreamworld built to keep us under control” Morpheus, early in The Matrix. “ In dreaming, you are not only out of control, you don’t even know it…I was completely duped again and again the minute my pons, my amygdala, my perihippocampal cortex, my anterior cingulate, my visual association and parietal opercular cortices were revved up and my dorsolateral prefrontal cortex was muffled” ” J. Allan Hobson, The Dream Drugstore, p.64 The Matrix is an exercise in (...) ambivalence, and at the very heart of that ambivalence lies the Dream. In our dreams, we are not in control. Real dreaming, unlike many popular philosophers’ fictions, is an altered state, closely related to the states induced by chemical manipulations such as the use of (certain) medical or recreational drugs. The dreaming brain is not like the wakeful brain. Normal sensory input is blocked, attentional capacities are impaired or lost, memory is distorted, reasoning and logic are weakened, narratives run wild, self-reflection is dampened or destroyed, emotion and instinct are hyperstimulated, and forms of ‘top-down’ willed control and decision-making diluted and easily overwhelmed. (shrink)

We tested the new threat simulation theory of the biological function of dreaming by analysing 592 dreams from 52 subjects with a rating scale developed for quantifying threatening events in dreams. The main predictions were that dreams contain more frequent and more severe threats than waking life does; that dream threats are realistic; and that they primarily threaten the Dream Self who tends to behave in a relevant defensive manner in response to them. These predictions were confirmed and the (...) theory empirically supported. We suggest that the threat simulation theory of dreaming may have wider implications for theories about the function of consciousness. (shrink)

Previous simulation models have found positive effects of cognitive diversity on group performance, but have not explored effects of diversity in demographics (e.g., gender, ethnicity). In this paper, we present an agent-based model that captures two empirically supported hypotheses about how demographic diversity can improve group performance. The results of our simulations suggest that, even when social identities are not associated with distinctive task-related cognitive resources, demographic diversity can, in certain circumstances, benefit collective performance by counteracting two types of (...) conformity that can arise in homogeneous groups: those relating to group-based trust and those connected to normative expectations towards in-groups. (shrink)

Ensemble musicians play in synchrony despite expressively motivated irregularities in timing. We hypothesized that synchrony is achieved by each performer internally simulating the concurrent actions of other ensemble members, relying initially on how they would perform in their stead. Hence, musicians should be better at synchronizing with recordings of their own earlier performances than with others’ recordings. We required pianists to record one part from each of several piano duets, and later to play the complementary part in synchrony with their (...) own or others’ recordings. The pianists were also asked to identify their own recordings. The pianists were better at synchronizing with their own than with others’ performances, and they were able to recognize their own recordings. Furthermore, synchronization accuracy and recognition were correlated: Pianists who were relatively accurate at synchronizing with their own performances were also good at recognizing them. Thus, action simulation may underlie both synchronization and self-recognition. (shrink)

This paper argues that at least one of the following propositions is true: the human species is very likely to go extinct before reaching a "posthuman" stage; any posthuman civilization is extremely unlikely to run a significant number of simulations of their evolutionary history ; we are almost certainly living in a computer simulation. It follows that the belief that there is a significant chance that we will one day become posthumans who run ancestor-simulations is false, unless we are (...) currently living in a simulation. A number of other consequences of this result are also discussed. (shrink)

When can macroscopic data about a system be used to set parameters in a microfoundational simulation? We examine the epistemic viability of tweaking parameter values to generate a better fit between the outcome of a simulation and the available observational data. We restrict our focus to microfoundational simulations—those simulations that attempt to replicate the macrobehavior of a target system by modeling interactions between microentities. We argue that tweaking can be effective but that there are two central risks. First, (...) tweaking risks overfitting the simulation to the data and thus compromising predictive accuracy; and second, it risks compromising the microfoundationality of the simulation. We evaluate standard responses to tweaking and propose strategies to guard against these risks. (shrink)

Mental time travel is defined as projecting the self into the past and the future. Despite growing evidence of the similarities of remembering past and imagining future events, dominant theories conceive of these as distinct capacities. I propose that memory and imagination are fundamentally the same process – constructive episodic simulation – and demonstrate that the ‘simulation system’ meets the three criteria of a neurocognitive system. Irrespective of whether one is remembering or imagining, the simulation system: acts (...) on the same information, drawing on elements of experience ranging from fine-grained perceptual details to coarser-grained conceptual information and schemas about the world; is governed by the same rules of operation, including associative processes that facilitate construction of a schematic scaffold, the event representation itself, and the dynamic interplay between the two ; and is subserved by the same brain system. I also propose that by forming associations between schemas, the simulation system constructs multi-dimensional cognitive spaces, within which any given simulation is mapped by the hippocampus. Finally, I suggest that simulation is a general capacity that underpins other domains of cognition, such as the perception of ongoing experience. This proposal has some important implications for the construct of ‘MTT’, suggesting that ‘time’ and ‘travel’ may not be defining, or even essential, features. Rather, it is the ‘mental’ rendering of experience that is the most fundamental function of this domain-general simulation system enabling humans to re-experience the past, pre-experience the future, and also comprehend the complexities of the present. (shrink)

In accounting for the way we explain and predict behavior, two major positions are the theory-theory and the simulation theory. Recently, several authors have advocated a hybrid position, where elements of both theory and simulation are part of the account. One popular strategy for incorporating simulation is to note that we sometimes assign mental states to others by performing cognitive operations in ourselves that mirror what has occurred in the target. In this article, I argue that this (...) way of thinking about simulation is misguided. The confusion stems from a failure to appreciate how the application of any internal theory, including folk psychology, requires the employment of other cognitive sub-systems and mechanisms. Just as we need to use our visual system to see what another person is seeing, so too we sometimes need to use our own internal sub-systems to ascertain facts about another's mental states. In many such cases, our cognitive mechanisms are used more as ?fact-finders? rather than as simulators. After spelling all this out, I offer two ways to demarcate cognitive processes that are real simulation from those that are simply used in the application of a theory. (shrink)

N. Bostrom’s simulation argument and two additional assumptions imply that we likely live in a computer simulation. The argument is based upon the following assumption about the workings of realistic brain simulations: The hardware of a computer on which a brain simulation is run bears a close analogy to the brain itself. To inquire whether this is so, I analyze how computer simulations trace processes in their targets. I describe simulations as fictional, mathematical, pictorial, and material models. (...) Even though the computer hardware does provide a material model of the target, this does not suffice to underwrite the simulation argument because the ways in which parts of the computer hardware interact during simulations do not resemble the ways in which neurons interact in the brain. Further, there are computer simulations of all kinds of systems, and it would be unreasonable to infer that some computers display consciousness just because they simulate brains rather than, say, galaxies. (shrink)

Based on a framework that distinguishes several types, roles and functions of values in science, we discuss legitimate applications of values in the validation of computer simulations. We argue that, first, epistemic valuesEpistemic values, such as empirical accuracyAccuracy and coherence with background knowledgeBackground knowledge, have the role to assess the credibilityCredibility of simulation results, whereas, second, cognitive valuesCognitive values, such as comprehensiveness of a conceptual modelConceptual model or easy handling of a numerical model, have the role to assess the (...) usefulness of a model for investigating a hypothesisHypothesis. In both roles, values perform what we call first-order functions. In addition, cognitive values may also serve an auxiliary function by facilitating the assessment of credibility. As for a third type of values, i.e. social valuesSocial values, their legitimate role consists in specifying and weighing epistemic and cognitive values with respect to practical uses of a simulation, which is considered a second-order function. Rational intersubjective agreementAgreement on how to specify and weigh the different values is supposed to ensure objectivity in simulation validation. (shrink)

Michael Weisberg has given us a lovely book on models. It has very broad coverage of issues intersecting the nature of models and their use, an extensive consideration of long ignored “concrete” models with a rich case study, a discussion and classification of the many diverse kinds of models, and a particularly groundbreaking and innovative discussion of similarity concerning how models relate to the world. Included are insightful discussions of increasingly used “agent based” models, and the conjoint use of multiple (...) models in looking for robust results. Weisberg fills in some discussions with modeling and simulation results of his own.In addition, he considers and critiques other recent competing views on models, including the increasingly popular “models as fictions” account. His discussion is clear and technically precise without being needlessly so, and his distinctions are useful. The scientist is more likely to recognize his objects than the semantic theorist, and that is how it .. (shrink)

The ArgumentIn its reconstruction of scientific practice, philosophy of science has traditionally placed scientific theories in a central role, and has reduced the problem of mediating between theories and the world to formal considerations. Many applications of scientific theories, however, involve complex mathematical models whose constitutive equations are analytically unsolvable. The study of these applications often consists in developing representations of the underlying physics on a computer, and using the techniques of computer simulation in order to learn about the (...) behavior of these systems. In many instances, these computer simulations are not simple number-crunching techniques. They involve a complex chain of inferences that serve to transform theoretical structures into specific concrete knowledge of physical systems. In this paper I argue that this process of transformation has its own epistemology. I also argue that this kind of epistemology is unfamiliar to most philosophy of science, which has traditionally concerned itself with the justification of theories, not with their application. Finally, I urge that the nature of this epistemology suggests that the end results of some simulations do not bear a simple, straightforward relation to the theories from which they stem. (shrink)

Can computer simulation results be evidence for hypotheses about real-world systems and phenomena? If so, what sort of evidence? Can we gain genuinely new knowledge of the world via simulation? I argue that evidence from computer simulation is aptly characterized as higher-order evidence: it is evidence that other evidence regarding a hypothesis about the world has been collected. Insofar as particular epistemic agents do not have this other evidence, it is possible that they will gain genuinely new (...) knowledge of the world via simulation. I illustrate with examples inspired by uses of simulation in meteorology and astrophysics. (shrink)

Studying drug relationships can provide deeper information for the construction and maintenance of biomedical databases and provide more important references for disease treatment and drug development. The research model has expanded from the previous focus on a certain drug to the systematic analysis of the pharmaceutical network formed between drugs. Network model is suitable for the study of the nonlinear relationship of the pharmaceutical relationship by modeling the data learning. Association rule mining is used to find the potential correlations between (...) the various sets of massive data. Therefore, based on the network model, this research proposed an algorithm for drug interaction under improved association rules, which achieved accurate analysis and decision-making of drug relationship. Meanwhile, this research applied the established association rule algorithm to discuss the relationship between Chinese medicine and mental illness medicine and conducted the algorithm research and simulation analysis of the association relationship. The results showed the association rule algorithm based on the network model constructed was better than other association algorithms. It had reliability and superiority in decision-making in improving the drug-drug relationship. It also promoted the rational use of medicines and played a guiding role in pharmaceutical research. This provides scientific research personnel with research basis and research ideas for disease-related diagnosis. (shrink)

This paper argues that at least one of the following propositions is true: (1) the human species is very likely to go extinct before reaching a “posthuman” stage; (2) any posthuman civilization is extremely unlikely to run a significant number of simulations of their evolutionary history (or variations thereof); (3) we are almost certainly living in a computer simulation. It follows that the belief that there is a significant chance that we will one day become posthumans who run ancestor-simulations (...) is false, unless we are currently living in a simulation. A number of other consequences of this result are also discussed. (shrink)

Collaborative filtering technology is currently the most successful and widely used technology in the recommendation system. It has achieved rapid development in theoretical research and practice. It selects information and similarity relationships based on the user’s history and collects others that are the same as the user’s hobbies. User’s evaluation information is to generate recommendations. The main research is the inadequate combination of context information and the mining of new points of interest in the context-aware recommendation process. On the basis (...) of traditional recommendation technology, in view of the characteristics of the context information in music recommendation, a personalized and personalized music based on popularity prediction is proposed. Recommended algorithm is MRAPP. The algorithm first analyzes the user’s contextual information under music recommendation and classifies and models the contextual information. The traditional content-based recommendation technology CB calculates the recommendation results and then, for the problem that content-based recommendation technology cannot recommend new points of interest for users, introduces the concept of popularity. First, we use the memory and forget function to reduce the score and then consider user attributes and product attributes to calculate similarity; secondly, we use logistic regression to train feature weights; finally, appropriate weights are used to combine user-based and item-based collaborative filtering recommendation results. Based on the above improvements, the improved collaborative filtering recommendation algorithm in this paper has greatly improved the prediction accuracy. Through theoretical proof and simulation experiments, the effectiveness of the MRAPP algorithm is demonstrated. (shrink)

Human resource management risks are due to the failure of employer organization to use relevant human resources reasonably and can result in tangible or intangible waste of human resources and even risks; therefore, constructing a practical early warning model of human resource management risk is extremely important for early risk prediction. The back propagation neural network is an information analysis and processing system formed by using the error back propagation algorithm to simulate the neural function and structure of the human (...) brain, which can handle complex and changeable things that do not have an obvious linear relationship between output results and input factors, so as to find the objective connection between the two. Based on the summary and analysis of previous research works, this article expounded the research status and significance of early warning for human resource management risks, elaborated the development background, current status, and future challenges of the BP neural network, introduced the method and principle of the BP neural network’s connection weight calculation and learning training, performed the risk inducement analysis, index system establishment, and network node selection of human resource management, constructed an early warning model of human resource management risk based on the BP neural network, conducted the risk warning model training and detection based on the BP neural network, and finally carried out a simulation and its result analysis. The study results show that the early warning model of human resource management risk based on the BP network is effective, and this trained and tested BP network risk warning model can be used to conduct early warning empirical research on human resource risks to prevent human resource risks, ensure enterprise’s benign operation, and at the same time play a role in supervision and promotion of market order rectification. (shrink)

In the Western tradition, at least since the 14th century, the philosophy of knowledge has been built around the idea of knowledge as a representation [BOU 99]. The question of the evaluation of knowledge refers at the same time (1) to the object represented (which one does one represent?), (2) to the process of knowledge formation, in particular with the role of the knowing subject (which one does one represent and how does one represent it?), and finally (3) to the (...) relationship between the representation and the represented object. Criteria of evaluation such as “validity”, “adequacy” or “truth”, as mentioned in [AMB 07], make sense only with respect to these three dimensions. An evaluation can thus (1) depend on the ontological nature of the object of knowledge, (2) relate to the relationship between subject and object—including the structures (cognitive, social) which organize this relationship, or (3) relate to the relation of similarity between the object and its representation as well. The relevant criteria of evaluation thus depend on the points of view adopted on these questions. As there are indeed a plurality of points of view in this field, the goal of this appendix is to summarize, as briefly as possible, the various positions adopted by the philosophers and to refer to the relevant texts of reference for more information (for a first outline [CHA 76, SCH 01]). The first section 1 introduces useful discussions about the philosophy of theoretical knowledge and general epistemology, from a quasi-historical perspective. Section two 2 discusses the intermediary but central notion of models. Section three 3, more exploratory, introduces an approach to simulation as “concrete experiment”. It suggests that such a frequent claim in the literature, when precisely evaluated, can, to some extent, renew both the representational and the linguistic views on simulation. (shrink)

In the Western tradition, at least since the 14th century, the philosophy of knowledge has been built around the idea of knowledge as a representation [Boulnois 1999]. The question of the evaluation of knowledge refers at the same time (1) to the object represented (which one does one represent?), (2) to the process of knowledge formation, in particular with the role of the knowing subject (which one does one represent and how does one represent it?), and finally (3) to the (...) relationship between the representation and the represented object. Criteria of evaluation such as “validity”, “adequacy” or “truth”, as mentioned in chapter 4, make sense only with respect to these three dimensions. An evaluation can thus (1) depend on the ontological nature of the object of knowledge, (2) relate to the relationship between subject and object—including the structures (cognitive, social) which organize this relationship, or (3) relate to the relation of similarity between the object and its representation as well. The relevant criteria of evaluation thus depend on the points of view adopted on these questions. As there are indeed a plurality of points of view in this field, the goal of this appendix is to summarize, as briefly as possible, the various positions adopted by the philosophers and to refer to the relevant texts of reference for more information. The first section introduces useful discussions about the philosophy of theoretical knowledge and general epistemology, from a quasi-historical perspective. Section two discusses the intermediary but central notion of models. Section three, more exploratory, intro-duces an approach to simulation as “concrete experiment”. It suggests that such a frequent claim in the literature, when precisely evaluated, can, to some extent, renew both the representational and the linguistic views on simulation. (shrink)

The spread of epidemics, especially COVID-19, is having a significant impact on the world. If an epidemic is not properly controlled at the beginning, it is likely to spread rapidly and widely through the coexistence relationship between natural and social systems. A university community is a special, micro-self-organized social system that is densely populated. However, university authorities in such an environment seem to be less cautious in the defence of an epidemic. Currently, there is almost no quantitative research on epidemic (...) spreading and response strategies in universities. In this paper, a case study of a university community is considered for a simulation of an infection evolving after an epidemic outbreak based on the method of system dynamics of the three stages. The results show the following: By improving the speed of the initial emergency response, the total number of patients can be effectively controlled. A quarantine policy helps to slow down the evolution of infection. The higher the isolation ratio, the higher the cost; therefore, the isolation ratio should be optimized. It is important to make emergency plans for controlling epidemic spreading and carry out emergency drills and assessments regularly. According to the results of this study, we suggest an emergency management framework for public health events in university communities. (shrink)

Business simulation games (BSGs) have been widely used in entrepreneurship education with positive effects. However, there are still some deficiencies in the BSGs, such as limited guidance, low uncertainty and limited simulation environment, which make it impossible to exert the maximum effect. Artificial intelligence (AI) can solve the above shortcomings. The combination of AI and BSGs is the possible development direction of BSGs. But how to effectively combine BSGs with AI is still an open question. Using a quasi-experimental (...) design, this study uses fuzzy-set qualitative comparative analysis to analyze how participants’ entrepreneurial attitude changes in BSGs. The results show that BSGs can effectively improve entrepreneurial attitude, and there are four types of promotion configurations. These four configurations consist of five antecedent conditions. According to the above conclusions, AI can improve entrepreneurial attitude in BSGs in various ways, such as simulating competitors, providing targeted feedback for failures, and improving game experience. The contribution of this paper is to highlight the possibility of combining AI with BSGs, and to provide suggestions on how AI can intervene in BSGs. (shrink)

Optimal strategy, one of the main transit assignment models, can better demonstrate the flexibility for passengers using routes in a transit network. According to the basic optimal strategy model, passengers can board trains based on their frequency without any capacity limitation. In the metropolitan cities such as Beijing, Shanghai, and Hong Kong, morning commuters face huge transit problems. Especially for the metro system, there is heavy rush in metro stations. Owing to the limited train capacity, some passengers cannot board the (...) first coming train and need to wait for the next one. To better demonstrate the behavior of passengers pertaining to the limited train capacity, we consider capacity constraints for the basic optimal strategy model to represent the real situation. We have proposed a simulation-based algorithm to solve the model and apply it to the Beijing Subway to demonstrate the feasibility of the model. The application of the proposed approach has been demonstrated using the computational results for transit networks originating from practice. (shrink)