The credibility of digital computer simulations has always been a problem. Today, through the debate on verification and validation, it has become a key issue. I will review the existing theses on that question. I will show that, due to the role of epistemological beliefs in science, no general agreement can be found on this matter. Hence, the complexity of the construction of sciences must be acknowledged. I illustrate these claims with a recent historical example. Finally I temperate this diversity (...) by insisting on recent trends in environmental sciences and in industrial sciences. (shrink)

Philosophy can shed light on mathematical modeling and the juxtaposition of modeling and empirical data. This paper explores three philosophical traditions of the structure of scientific theory—Syntactic, Semantic, and Pragmatic—to show that each illuminates mathematical modeling. The Pragmatic View identifies four critical functions of mathematical modeling: (1) unification of both models and data, (2) model fitting to data, (3) mechanism identification accounting for observation, and (4) prediction of future observations. Such facets are explored using a recent (...) exchange between two groups of mathematical modelers in plant biology. Scientific debate can arise from different modeling philosophies. (shrink)

Shell tube surface condenser (STSC) is a heat exchanger system that exchange a high pressure steam into low pressure water and it is widely used in applications like textile industries and nuclear power plants. The modelling of the system has been established based on lumped parameters. In this paper, a fuzzy expert system is developed in order to improve the performance of the condenser. A pressure feedback system has been developed to analyze the effect of the condenser output temperature, circulating (...) water flow and heat developed. An experiment has been made for the closed loop system using fuzzy tuned PI, fuzzy logic and PID controllers and a promising results have been obtained successfully. (shrink)

The spatial-ecological modeling is relating sustainable dispersions with social development. Sustainability with spatial-ecological model gives attention to urban environments in the design review management to comply with Earth’s system. Naturally exchanged patterns of ecosystems have consistent and periodic cycles to preserve energy flows and materials in Earth’s system. The Probabilistic Risk Assessment (PRA) technique is utilized to assess the safety of an industrial complex. The other analytical approach is the Failure-Safe Mode and Effect Analysis (FMEA) for critical components. The (...) plant safety parameters are identified for engineering topology as employed in assessment safety of industrial ecology. In particular, the most severe accidental release of hazardous gaseous is postulated, analyzed and assessment in industrial region. The IAEA-safety assessment procedure is used to account the duration and rate of discharge of liquid chlorine. The ecological model of plume dispersion width and concentration of chlorine gas in the downwind direction is determined using Gaussian Plume Model in urban and rural areas and presented with SURFER®. The prediction of accident consequences is traced in risk contour concentration lines. The local greenhouse effect is predicted with relevant conclusions. The spatial-ecological model is predicted for multiple factors distribution schemes of multi-criteria analysis. The input–output analysis is explored from the spillover effect, and we conducted Monte Carlo simulations for sensitivity analysis. Their unique structure is balanced within “equilibrium patterns”, such as the composite index for biosphere with collective structure of many distributed feedback flows. These dynamic structures are related to have their physical and chemical properties and enable a gradual and prolonged incremental pattern. While this spatial model structure argues from ecology, resource savings, static load design, financial and other pragmatic reasons, the outcomes are not decisive in an artistic/architectural perspective. The hypothesis is deployed to unify analytic and analogical spatial structure in development urban environments using optimization loads as an example of integrated industrial structure where the process is based on engineering topology of systems ecology. (shrink)

High grade chromite ore has been decreased constantly due to the importance of chromium element in industrial uses such as metallurgical, chemical, and refractory industries. Therefore, beneficiation of low grade has been more significant .Response Surface Methodology (RSM) is combination of statistical and mathematical methods used for modeling and analyzing problems. In this study, the Central Composite Design (CCD) was applied by using Design-Expert (version 6.0.5) for modeling and optimizing the effect of operating variables on the performance of (...) gravity separation via pilot plant shaking table for chromite ore. Three operating variables were studied, namely feed rate, tilt angle, and flow rate during the tests. The sample under study is low grade chromite ore, containing (30.21%, Cr2O3). The mathematical model equations of ANOVA model revealed that the grade of concentrate is more sensetive for feed rate (g/min) compered to water flow rate (l/min).whereas , recovery of concentrate is more sensetive for tilt angle compered to water flow rate (l/min) and feed rate (g/min). Optimized responses for the beneficiation process were found at concentrate with 48.52% Cr2O3 in with 83.09% recovery and it was achieved at water flow rate 15.33 l/min, tilt angle 2.16 ≈ 2.00 degree, and feed rate of 195.38 g/min. (shrink)

There are long-standing doubts about whether data from subjective scales—for instance, self-reports of happiness—are cardinally comparable. It is unclear how to assess whether these doubts are justified without first addressing two unresolved theoretical questions: how do people interpret subjective scales? Which assumptions are required for cardinal comparability? This paper offers answers to both. It proposes an explanation for scale interpretation derived from philosophy of language and game theory. In short: conversation is a cooperative endeavour governed by various maxims (Grice 1989); (...) because subjective scales are vague and individuals want to make themselves understood, scale interpretation is a search for a focal point (Schelling 1960). A specific focal point it hypothesised; if this hypothesis is correct, subjective data will be cardinally comparable. Four individually necessary and jointly sufficient conditions for cardinal comparability are specified. The paper then argues this hypothesis can be empirically be tested, makes an initial attempt to do so using subjective well-being data, and concludes it is supported. Numerous areas for further research are identified including, at the end of the paper, how certain tests could be used to ‘correct’ subjective data if they are not cardinal. (shrink)

While life satisfaction theories (LSTs) of well-being are barely discussed in philosophy, they are popular among social scientists and wider society. When philosophers have discussed LSTs, they are taken to be a distinct alternative to the three canonical accounts of well-being—hedonism, desire theories, the objective list. This essay makes three main claims. First, on closer inspection, LSTs are indistinguishable from a type of desire theory—the global desire theory. Second, the life satisfaction/global desire theories are the only subjectivist accounts of well-being (...) in the sense that they maintain individuals decide what makes their lives go well for them; hedonism and other desire theories are subjectivist only in some alternative senses. Third, subjectivism is implausible, although for different reasons from those that are usually given. I examine what I take to be the two main current objections to LSTs and argue that they are unproblematic. I then raise two different, challenging objections. The first is novel. The second has been noted in passing, but its seriousness underestimated. I close by sketching some non-obvious difficulties that subjectivists will face if they attempt to show rival objectivist theories suffer even more counterintuitive implications. Although subjectivism has a strong intuitive pull, we should be ready to abandon it in favour of an objectivist theory—although it is not my purpose here to say which one. (shrink)

Suppose you want to do as much good as possible. What should you do? According to members of the effective altruism movement—which has produced much of the thinking on this issue and counts several moral philosophers as its key protagonists—we should prioritise among the world’s problems by assessing their scale, solvability, and neglectedness. Once we’ve done this, the three top priorities, not necessarily in this order, are (1) aiding the world’s poorest people by providing life-saving medical treatments or alleviating poverty (...) itself, (2) preventing global catastrophic risks, such as those posed by nuclear war or rogue artificial intelligence, and (3) ending factory farming. These claims are both plausible and striking. If correct, they should prompt a stark revision of how we approach our altruistic activities. However, the project of determining how to do the most good—as opposed to say, whether we should do the most good—has only recently, within the last ten years, become the subject of serious academic attention. Many key claims have not yet been carefully scrutinised. This is a cause for concern: are effective altruists doing good badly? In this thesis, I critique and develop some of the latest claims about how individuals can do the most good. I do this in three areas: the value of saving lives (preventing premature deaths), how best to improve lives (making people happier during their lives), and cause prioritisation methodology (frameworks for determining which problems are the highest priorities). In each case, I raise novel theoretical considerations that, when incorporated, change the analysis. Roughly speaking, my main conclusions are (1) saving lives is not as straightforwardly good we tend to suppose, may not be good at all, and is not clearly a priority; (2) happiness can be measured through self-reports and, based on the self-reported evidence, treating mental health stands out as an overlooked problem that may be an even more cost-effective way to improve lives than alleviating poverty; (3) the cause prioritisation methodology proposed by effective altruists needs to be moderately reconceptualised and, when it is, it turns out it is not as illuminating a tool as we might have thought and hoped. (shrink)

As well as disagreeing about how much one should donate to charity, moral theories also disagree about where one should donate. In light of this disagreement, how should the morally uncertain philanthropist allocate her donations? In many cases, one intuitively attractive option is for the philanthropist to split her donations across all of the charities that are recommended by moral views in which she has positive credence, with each charity’s share being proportional to her credence in the moral theories that (...) recommend that particular charity. Despite the fact that something like this approach is already being used by real-world philanthropists to distribute billions of dollars of donations, it is not supported by any of the approaches to moral uncertainty that have been proposed thus-far in the philosophical literature. In this paper, we will develop a bargaining-based approach to moral uncertainty that honors the proportionality intuition in favor of splitting one’s donations. We also show how this bargaining-based approach has several further advantages over the best alternative proposals. (shrink)

What is the class of possible semiotic systems? What kinds of systems could count as such systems? The human mind is naturally considered the prototypical semiotic system. During years of research in semiotics the class has been broadened to include i.e. living systems like animals, or even plants. It is suggested in the literature on artificial intelligence that artificial agents are typical examples of symbol-processing entities. It also seems that semiotic processes are in fact cognitive processes. In consequence, it is (...) natural to ask the question about the relation between semiotic studies and research on artificial cognitive systems within cognitive science. Consequently, my main question concerns the problem of inclusion or exclusion from the semiotic spectrum at least some artificial systems. I would like to consider some arguments against the possibility of artificial semiotic systems and I will try to repeal them. Then I will present an existing natural-language using agent of the SNePS system and interpret it in terms of Peircean theory of signs. I would like also to show that some properties of semiotic systems in Peircean sense could be also found in a discussed artificial system. Finally, I will have some remarks on the status of semiotics in general. (shrink)

Possibility semantics offers an elegant framework for a semantic analysis of modal logic that does not recruit fully determinate entities such as possible worlds. The present papers considers the application of possibility semantics to the modeling of the indeterminacy of the future. Interesting theoretical problems arise in connection to the addition of object-language determinacy operator. We argue that adding a two-dimensional layer to possibility semantics can help solve these problems. The resulting system assigns to the two-dimensional determinacy operator a (...) well-known logic (coinciding with the logic of universal modalities under global consequence). The paper concludes with some preliminary inroads into the question of how to distinguish two-dimensional possibility semantics from the more established branching framework. (shrink)

Experimental activity is traditionally identified with testing the empirical implications or numerical simulations of models against data. In critical reaction to the ‘tribunal view’ on experiments, this essay will show the constructive contribution of experimental activity to the processes of modeling and simulating. Based on the analysis of a case in fluid mechanics, it will focus specifically on two aspects. The first is the controversial specification of the conditions in which the data are to be obtained. The second is (...) conceptual clarification, with a redefinition of concepts central to the understanding of the phenomenon and the conditions of its occurrence. (shrink)

The topics of modeling and information come together in at least two ways. Computational modeling and simulation play an increasingly important role in science, across disciplines from mathematics through physics to economics and political science. The philosophical questions at issue are questions as to what modeling and simulation are adding, altering, or amplifying in terms of scientific information. What changes with regard to information acquisition, theoretical development, or empirical confirmation with contemporary tools of computational modeling? In (...) this sense the title of this article is read in the following way: What kind of information is modeling information? What kind of information does modeling give us? (shrink)

The problem of plant individuality is something which has vexed botanists throughout the ages, with fashion swinging back and forth from treating plants as communities of individuals (Darwin 1800 ; Braun and Stone 1853 ; Münch 1938 ) to treating them as organisms in their own right, and although the latter view has dominated mainstream thought most recently (Harper 1977 ; Cook 1985 ; Ariew and Lewontin 2004 ), a lively debate conducted mostly in Scandinavian journals proves that the (...) issues are far from being resolved (Tuomi and Vuorisalo 1989b ; Fagerström 1992 ; Pan and Price 2001 ). In this paper I settle the matter once and for all, by showing which elements of each side are correct. (shrink)

According to F. Adams [this journal, vol. 68, 2018] cognition cannot be realized in plants or bacteria. In his view, plants and bacteria respond to the here-and-now in a hardwired, inflexible manner, and are therefore incapable of cognitive activity. This article takes issue with the pursuit of plant cognition from the perspective of an empirically informed philosophy of plant neurobiology. As we argue, empirical evidence shows, contra Adams, that plant behavior is in many ways analogous to animal (...) behavior. This renders plants suitable to be described as cognitive agents in a non-metaphorical way. Sections two to four review the arguments offered by Adams in light of scientific evidence on plant adaptive behavior, decision-making, anticipation, as well as learning and memory. Section five introduces the ‘phyto-nervous’ system of plants. To conclude, section six resituates the quest for plant cognition into a broader approach in cognitive science, as represented by enactive and ecological schools of thought. Overall, we aim to motivate the idea that plants may be considered genuine cognitive agents. Our hope is to help propel public awareness and discussion of plant intelligence once appropriately stripped of anthropocentric preconceptions of the sort that Adams' position appears to exemplify. (shrink)

Causal Modeling Semantics (CMS, e.g., Galles and Pearl 1998; Pearl 2000; Halpern 2000) is a powerful framework for evaluating counterfactuals whose antecedent is a conjunction of atomic formulas. We extend CMS to an evaluation of the probability of counterfactuals with disjunctive antecedents, and more generally, to counterfactuals whose antecedent is an arbitrary Boolean combination of atomic formulas. Our main idea is to assign a probability to a counterfactual (A ∨ B) > C at a causal model M as a (...) weighted average of the probability of C in those submodels that truthmake A∨ B (Briggs 2012; Fine 2016, 2017). The weights of the submodels are given by the inverse distance to the original model M, based on a distance metric proposed by Eva, Stern, and Hartmann (2019). Apart from solving a major problem in the epistemology of counterfactuals, our paper shows how work in semantics, causal inference and formal epistemology can be fruitfully combined. (shrink)

All living things have sensory capacities. Plants, in particular, have sensory receptors, transduce the activations of these receptors, and process these outputs in order to manage actions that demand sensory integration. However, there is a kind of sensory function that plants cannot perform. They cannot sense something as other than themselves. Animals, by contrast, perceive. They experience two kinds of "othering impressions"—impressions of entities as located outside and available for interaction, and hence as distinct from the perceiving subject. First, they (...) represent external entities in a "body scheme" that enables sensorimotor interaction with these entities. Second, higher animals such as mammals and birds and possibly fish, represent these entities as located relative to a "cognitive map." These othering impressions are very important because they are the foundation for the human conceptions of the self and other. (shrink)

Experimental modeling in biology involves the use of living organisms (not necessarily so-called "model organisms") in order to model or simulate biological processes. I argue here that experimental modeling is a bona fide form of scientific modeling that plays an epistemic role that is distinct from that of ordinary biological experiments. What distinguishes them from ordinary experiments is that they use what I call "in vivo representations" where one kind of causal process is used to stand in (...) for a physically different kind of process. I discuss the advantages of this approach in the context of evolutionary biology. (shrink)

The Plant Ontology (PO; http://www.plantontology.org/) is a publicly-available, collaborative effort to develop and maintain a controlled, structured vocabulary (“ontology”) of terms to describe plant anatomy, morphology and the stages of plant development. The goals of the PO are to link (annotate) gene expression and phenotype data to plant structures and stages of plant development, using the data model adopted by the Gene Ontology. From its original design covering only rice, maize and Arabidopsis, the scope of (...) the PO has been expanded to include all green plants. The PO was the first multi-species anatomy ontology developed for the annotation of genes and phenotypes. Also, to our knowledge, it was one of the first biological ontologies that provides translations (via synonyms) in non-English languages such as Japanese and Spanish. There are about 2.2 million annotations linking PO terms to over 110,000 unique data objects representing genes or gene models, proteins, RNAs, germplasm and Quantitative Traits Loci (QTLs) from 22 plant species. In this paper, we focus on the plant anatomical entity branch of the PO, describing the organizing principles, resources available to users, and examples of how the PO is integrated into other plant genomics databases and web portals. We also provide two examples of comparative analyses, demonstrating how the ontology structure and PO-annotated data can be used to discover the patterns of expression of the LEAFY (LFY) and terpene synthase (TPS) gene homologs. (shrink)

Do plants represent according to Kant? This is closely connected to the question of whether he held plants are alive, because he explains life in terms of the faculty to act on one’s own representations. He also explains life as having an immaterial principle of self-motion, and as a body’s interaction with a supersensible soul. I argue that because of the way plants move themselves, Kant is committed to their being alive, to their having a supersensible ground of their self-activity, (...) and to their having desires (although these are not conscious). This has important ramifications for Kant’s teleology and philosophy of mind. (shrink)

The Plant Ontology (PO) is a community resource consisting of standardized terms, definitions, and logical relations describing plant structures and development stages, augmented by a large database of annotations from genomic and phenomic studies. This paper describes the structure of the ontology and the design principles we used in constructing PO terms for plant development stages. It also provides details of the methodology and rationale behind our revision and expansion of the PO to cover development stages for (...) all plants, particularly the land plants (bryophytes through angiosperms). As a case study to illustrate the general approach, we examine variation in gene expression across embryo development stages in Arabidopsis and maize, demonstrating how the PO can be used to compare patterns of expression across stages and in developmentally different species. Although many genes appear to be active throughout embryo development, we identified a small set of uniquely expressed genes for each stage of embryo development and also between the two species. Evaluating the different sets of genes expressed during embryo development in Arabidopsis or maize may inform future studies of the divergent developmental pathways observed in monocotyledonous versus dicotyledonous species. The PO and its annotation databasemake plant data for any species more discoverable and accessible through common formats, thus providing support for applications in plant pathology, image analysis, and comparative development and evolution. (shrink)

Plants from a handful of species provide the primary source of food for all people, yet this source is vulnerable to multiple stressors, such as disease, drought, and nutrient deficiency. With rapid population growth and climate uncertainty, the need to produce crops that can tolerate or resist plant stressors is more crucial than ever. Traditional plant breeding methods may not be sufficient to overcome this challenge, and methods such as highOthroughput sequencing and automated scoring of phenotypes can provide (...) significant new insights. Ontologies are essential tools for accessing and analysing the large quantities of data that come with these newer methods. As part of a larger project to develop ontologies that describe plant phenotypes and stresses, we are developing a plant disease extension of the Infectious Disease Ontology (IDOPlant). The IDOPlant is envisioned as a reference ontology designed to cover any plant infectious disease. In addition to novel terms for infectious diseases, IDOPlant includes terms imported from other ontologies that describe plants, pathogens, and vectors, the geographic location and ecology of diseases and hosts, and molecular functions and interactions of hosts and pathogens. To encompass this range of data, we are suggesting inOhouse ontology development complemented with reuse of terms from orthogonal ontologies developed as part of the Open Biomedical Ontologies (OBO) Foundry. The study of plant diseases provides an example of how an ontological framework can be used to model complex biological phenomena such as plant disease, and how plant infectious diseases differ from, and are similar to, infectious diseases in other organism. (shrink)

The fate of optimality modeling is typically linked to that of adaptationism: the two are thought to stand or fall together (Gould and Lewontin, Proc Relig Soc Lond 205:581–598, 1979; Orzack and Sober, Am Nat 143(3):361–380, 1994). I argue here that this is mistaken. The debate over adaptationism has tended to focus on one particular use of optimality models, which I refer to here as their strong use. The strong use of an optimality model involves the claim that selection (...) is the only important influence on the evolutionary outcome in question and is thus linked to adaptationism. However, biologists seldom intend this strong use of optimality models. One common alternative that I term the weak use simply involves the claim that an optimality model accurately represents the role of selection in bringing about the outcome. This and other weaker uses of optimality models insulate the optimality approach from criticisms of adaptationism, and they account for the prominence of optimality modeling (broadly construed) in population biology. The centrality of these uses of optimality models ensures a continuing role for the optimality approach, regardless of the fate of adaptationism. (shrink)

Naturalistic theories of representation seek to specify the conditions that must be met for an entity to represent another entity. Although these approaches have been relatively successful in certain areas, such as communication theory or genetics, many doubt that they can be employed to naturalize complex cognitive representations. In this essay I identify some of the difficulties for developing a teleosemantic theory of cognitive representations and provide a strategy for accommodating them: to look into models of signaling in evolutionary game (...) theory. I show how these models can be used to formulate teleosemantics and expand it in new directions. (shrink)

Computational modeling should play a central role in philosophy. In this introduction to our topical collection, we propose a small topology of computational modeling in philosophy in general, and show how the various contributions to our topical collection fit into this overall picture. On this basis, we describe some of the ways in which computational models from other disciplines have found their way into philosophy, and how the principles one found here still underlie current trends in the field. (...) Moreover, we argue that philosophers contribute to computational modeling not only by building their own models, but also by thinking about the various applications of the method in philosophy and the sciences. In this context, we note that models in philosophy are usually simple, while models in the sciences are often more complex and empirically grounded. Bridging certain methodological gaps that arise from this discrepancy may prove to be challenging and fruitful for the further development of computational modeling in philosophy and beyond. (shrink)

This chapter develops the idea that the germ-soma split and the suppression of individual fitness differences within the corporate entity are not always essential steps in the evolution of corporate individuals. It illustrates some consequences for multilevel selection theory. It presents evidence that genetic heterogeneity may not always be a barrier to successful functioning as a higher-level individual. This chapter shows that levels-of-selection theorists are wrong to assume that the central problem in transitions is always that of minimizing within-group competition. (...) Evidence of intralevel conflict does not qualify as evidence against the existence of a higher level of selection. (shrink)

This paper brings together Thompson's naive action explanation with interventionist modeling of causal structure to show how they work together to produce causal models that go beyond current modeling capabilities, when applied to specifically selected systems. By deploying well-justified assumptions about rationalization, we can strengthen existing causal modeling techniques' inferential power in cases where we take ourselves to be modeling causal systems that also involve actions. The internal connection between means and end exhibited in naive action (...) explanation has a modal strength like that of distinctively mathematical explanation, rather than that of causal explanation. Because it is stronger than causation, it can be treated as if it were merely causal in a causal model without thereby overextending the justification it can provide for inferences. This chapter introduces and demonstrate the usage of the Rationalization condition in causal modeling, where it is apt for the system(s) being modeled, and to provide the basics for incorporating R variables into systems of variables and R arrows into DAGs. Use of the Rationalization condition supplements causal analysis with action analysis where it is apt. (shrink)

The Plant Ontology (PO) (http://www.plantontology.org) (Jaiswal et al., 2005; Avraham et al., 2008) was designed to facilitate cross-database querying and to foster consistent use of plant-specific terminology in annotation. As new data are generated from the ever-expanding list of plant genome projects, the need for a consistent, cross-taxon vocabulary has grown. To meet this need, the PO is being expanded to represent all plants. This is the first ontology designed to encompass anatomical structures as well as growth (...) and developmental stages across such a broad taxonomic range. While other ontologies such as the Gene Ontology (GO) (The Gene Ontology Consortium, 2010) or Cell Type Ontology (CL) (Bard et al., 2005) cover all living organisms, they are confined to structures at the cellular level and below. The diversity of growth forms and life histories within plants presents a challenge, but also provides unique opportunities to study developmental and evolutionary homology across organisms. (shrink)

In recent years, the emergence of a new trend in contemporary philosophy has been observed in the increasing usage of empirical research methods to conduct philosophical inquiries. Although philosophers primarily use secondary data from other disciplines or apply quantitative methods (experiments, surveys, etc.), the rise of qualitative methods (e.g., in-depth interviews, participant observations and qualitative text analysis) can also be observed. In this paper, I focus on how qualitative research methods can be applied within philosophy of science, namely within the (...) philosophical debate on modeling. Specifically, I review my empirical investigations into the issues of model de-idealization, model justification and performativity. (shrink)

Research in experimental philosophy has increasingly been turning to corpus methods to produce evidence for empirical claims, as they open up new possibilities for testing linguistic claims or studying concepts across time and cultures. The present article reviews the quasi-experimental studies that have been done using textual data from corpora in philosophy, with an eye for the modeling and experimental design that enable statistical inference. I find that most studies forego comparisons that could control for confounds, and that only (...) a little less than half employ statistical testing methods to control for chance results. Furthermore, at least some researchers make modeling decisions that either do not take into account the nature of corpora and of the word-concept relationship, or undermine the experiment's capacity to answer research questions. I suggest that corpus methods could both provide more powerful evidence and gain more mainstream acceptance by improving their modeling practices. (shrink)

Although there have been efforts to integrate Semantic Web technologies and artificial agents related AI research approaches, they remain relatively isolated from each other. Herein, we introduce a new ontology framework designed to support the knowledge representation of artificial agents’ actions within the context of the actions of other autonomous agents and inspired by standard cognitive architectures. The framework consists of four parts: 1) an event ontology for information pertaining to actions and events; 2) an epistemic ontology containing facts about (...) knowledge, beliefs, perceptions and communication; 3) an ontology concerning future intentions, desires, and aversions; and, finally, 4) a deontic ontology for modeling obligations and prohibitions which limit agents’ actions. The architecture of the ontology framework is inspired by deontic cognitive event calculus as well as epistemic and deontic logic. We also describe a case study in which the proposed DCEO ontology supports autonomous vehicle navigation. (shrink)

Intellectualists about knowledge how argue that knowing how to do something is knowing the content of a proposition (i.e, a fact). An important component of this view is the idea that propositional knowledge is translated into behavior when it is presented to the mind in a peculiarly practical way. Until recently, however, intellectualists have not said much about what it means for propositional knowledge to be entertained under thought's practical guise. Carlotta Pavese fills this gap in the intellectualist view by (...) modeling practical modes of thought after Fregean senses. In this paper, I take up her model and the presuppositions it is built upon, arguing that her view of practical thought is not positioned to account for much of what human agents are able to do. (shrink)

The optimality approach to modeling natural selection has been criticized by many biologists and philosophers of biology. For instance, Lewontin (1979) argues that the optimality approach is a shortcut that will be replaced by models incorporating genetic information, if and when such models become available. In contrast, I think that optimality models have a permanent role in evolutionary study. I base my argument for this claim on what I think it takes to best explain an event. In certain contexts, (...) optimality and game-theoretic models best explain some central types of evolutionary phenomena. ‡Thanks to Michael Friedman, Helen Longino, Michael Weisberg, and especially Elliott Sober for comments on earlier drafts of this paper. †To contact the author, please write to: Department of Philosophy, Stanford University, Stanford, CA 94305-2155; e-mail: [email protected]. (shrink)

Logics based on weak Kleene algebra (WKA) and related structures have been recently proposed as a tool for reasoning about flaws in computer programs. The key element of this proposal is the presence, in WKA and related structures, of a non-classical truth-value that is “contaminating” in the sense that whenever the value is assigned to a formula ϕ, any complex formula in which ϕ appears is assigned that value as well. Under such interpretations, the contaminating states represent occurrences of a (...) flaw. However, since different programs and machines can interact with (or be nested into) one another, we need to account for different kind of errors, and this calls for an evaluation of systems with multiple contaminating values. In this paper, we make steps toward these evaluation systems by considering two logics, HYB1 and HYB2, whose semantic interpretations account for two contaminating values beside classical values 0 and 1. In particular, we provide two main formal contributions. First, we give a characterization of their relations of (multiple-conclusion) logical consequence—that is, necessary and sufficient conditions for a set Δ of formulas to logically follow from a set Γ of formulas in HYB1 or HYB2 . Second, we provide sound and complete sequent calculi for the two logics. (shrink)

Many in philosophy understand truth in terms of precise semantic values, true propositions. Following Braun and Sider, I say that in this sense almost nothing we say is, literally, true. I take the stand that this account of truth nonetheless constitutes a vitally useful idealization in understanding many features of the structure of language. The Fregean problem discussed by Braun and Sider concerns issues about application of language to the world. In understanding these issues I propose an alternative modeling (...) tool summarized in the idea that inaccuracy of statements can be accommodated by their imprecision. This yields a pragmatist account of truth, but one not subject to the usual counterexamples. The account can also be viewed as an elaborated error theory. The paper addresses some prima facie objections and concludes with implications for how we address certain problems in philosophy. (shrink)

Unlike any other field, the science of morality has drawn attention from an extraordinarily diverse set of disciplines. An interdisciplinary research program has formed in which economists, biologists, neuroscientists, psychologists, and even philosophers have been eager to provide answers to puzzling questions raised by the existence of human morality. Models and simulations, for a variety of reasons, have played various important roles in this endeavor. Their use, however, has sometimes been deemed as useless, trivial and inadequate. The role of models (...) in the science of morality has been vastly underappreciated. This omission shall be remedied here, offering a much more positive picture on the contributions modelers made to our understanding of morality. (shrink)

Conscious experiences are characterized by mental qualities, such as those involved in seeing red, feeling pain, or smelling cinnamon. The standard framework for modeling mental qualities represents them via points in geometrical spaces, where distances between points inversely correspond to degrees of phenomenal similarity. This paper argues that the standard framework is structurally inadequate and develops a new framework that is more powerful and flexible. The core problem for the standard framework is that it cannot capture precision structure: for (...) example, consider the phenomenal contrast between seeing an object as crimson in foveal vision versus merely as red in peripheral vision. The solution I favor is to model mental qualities using regions, rather than points. I explain how this seemingly simple formal innovation not only provides a natural way of modeling precision, but also yields a variety of further theoretical fruits: it enables us to formulate novel hypotheses about the space and structures of mental qualities, formally differentiate two dimensions of phenomenal similarity, generate a quantitative model of the phenomenal sorites, and define a measure of discriminatory grain. A noteworthy consequence is that the structure of the mental qualities of conscious experiences is fundamentally different from the structure of the perceptible qualities of external objects. (shrink)

Since the sixties, computational modeling has become increasingly important in both the physical and the social sciences, particularly in physics, theoretical biology, sociology, and economics. Sine the eighties, philosophers too have begun to apply computational modeling to questions in logic, epistemology, philosophy of science, philosophy of mind, philosophy of language, philosophy of biology, ethics, and social and political philosophy. This chapter analyzes a selection of interesting examples in some of those areas.

This is an article in Thomas J.J. McCloughlin (Ed.) The Nature of Science in Biology: A Resource for Educators. Graphikon Teo, Dublin. -/- Abstract: Philosophers usually tend to think of animals when they think about life, plants often only appear in their works as on the margins, in the background; they are rarely in the centre. However, plant life involves unique processes, including remarkable modes of interaction between plants and their environments. Needless to say, plants are vital parts of (...) ecosystems. Serious attention to plants provides novel and interesting perspectives on many topics in philosophy of biology, including individuality, organisation and disease. Plant biology should have a substantial part in philosophy education. To support this assertion, this paper briefly describes three topics related to plant-environment interaction and explains some of their philosophical implications. These topics are growth, plant hormones and plant-plant microbiota interactions, all of which present crucial aspects related to some prevalent topics in philosophy of biology such as individuality, systems thinking, and holobiont. (shrink)

We apply spatialized game theory and multi-agent computational modeling as philosophical tools: (1) for assessing the primary social psychological hypothesis regarding prejudice reduction, and (2) for pursuing a deeper understanding of the basic mechanisms of prejudice reduction.

It has recently been asserted that legislative moves to consider plants as ethical subjects are philosophically foolish because plants lack autonomy. While by no means the sole basis or driving criterion for moral behavior, it is possible to directly challenge skeptical attitudes by constructing a human-plant ethics centered on fundamental notions of autonomy. Autonomous beings are agents who rule themselves, principally for their own purposes. A considerable body of evidence in the plant sciences is increasingly recognizing the capacity (...) of plants to assess, perceive, and act on their environment. The primary purpose of their doing so is to generate the conditions for their own flourishing. With these plant purposes in mind, it is evidentially inappropriate to treat plants purely as instruments. In this age of environmental crisis, knowledge of plant intelligence and autonomy opens up a new debate on respecting and promoting the well-being of the plants that make life on Earth possible. (shrink)

Le texte suivant s'appuie assez largement sur des informations scientifiques de la biologie végétale. Ce choix de philosopher à partir de la technicité et de l'historicité des objets botaniques correspond à un parti pris. La proximité de l’humain à ses objets d’étude, sa tendance à anthropomorphiser, voire anthropocentrer, les observations ou les problèmes qui se présentent à lui, a fait l’objet de multiples réflexions philosophiques et épistémologiques. Kant, pour qui « tout intérêt est finalement pratique [...] même celui de la (...) raison spéculative n’est que conditionné et n’est complet que dans l’usage pratique » 1 , Bachelard, qui appelle à « substituer à la notion anthropomorphe de cause la notion scientifique de fonction » 2 , ou Canguilhem pour qui « l’anthropocentrisme est plus aisé à rejeter que l’anthropomorphisme [...] Peut-on être biologistes sans se sentir du côté des vivants ? » 3 . Ces réflexions ne sont-elles pas toujours centrées sur les modes de connaissance ou de pensée de l’humain, alors que les « objets d’étude » en question demeurent souvent dans un certain flou, voire une large indétermination ? La démarche suivie ici tente d’aller dans une autre direction. Elle interroge les effets de l’anthropocentrisation d’objets spécifiques à la biologie végétale, envisagée aussi bien dans sa profondeur historique que dans ses développements techniques récents. Nous tentons ici un pari : une analyse précise de nos connaissances botaniques, actuelles et passées, peut nourrir la réflexion philosophique sur notre rapport aux plantes et, à travers elles, sur nous-mêmes. (shrink)

Abstract: This research employs a Random Forest classification model to predict and assess obesity and cardiovascular disease (CVD) risk based on a comprehensive dataset collected from individuals in Mexico, Peru, and Colombia. The dataset comprises 17 attributes, including information on eating habits, physical condition, gender, age, height, and weight. The study focuses on classifying individuals into different health risk categories using machine learning algorithms. Our Random Forest model achieved remarkable performance with an accuracy, F1-score, recall, and precision all reaching 97.23%. (...) The model's success is attributed to its ability to effectively leverage attributes related to eating habits, physical condition, and demographic factors. Feature importance analysis reveals key factors contributing to accurate predictions. This paper contributes to the field of health analytics by demonstrating the effectiveness of Random Forest in predicting and categorizing health risks. The insights gained from this research have the potential to inform personalized health interventions and contribute to the advancement of precision health strategies. Furthermore, the study highlights the importance of leveraging machine learning techniques for health risk assessment in diverse populations. (shrink)

Real-world economies are open-ended dynamic systems consisting of heterogeneous interacting participants. Human participants are decision-makers who strategically take into account the past actions and potential future actions of other participants. All participants are forced to be locally constructive, meaning their actions at any given time must be based on their local states; and participant actions at any given time affect future local states. Taken together, these essential properties imply real-world economies are locally-constructive sequential games. This paper discusses a modeling (...) approach, Agent-based Computational Economics, that permits researchers to study economic systems from this point of view. ACE modeling principles and objectives are first concisely presented and explained. The remainder of the paper then highlights challenging issues and edgier explorations that ACE researchers are currently pursuing. (shrink)

Recent developments in vision science have resulted in several major changes in our understanding of human visual perception. For example, attention no longer appears necessary for "visual intelligence"--a large amount of sophisticated processing can be done without it. Scene perception no longer appears to involve static, general-purpose descriptions, but instead may involve dynamic representations whose content depends on the individual and the task. And vision itself no longer appears to be limited to the production of a conscious "picture"--it may also (...) guide processes outside the conscious awareness of the observer. (shrink)

Recently, Bechtel and Abrahamsen have argued that mathematical models study the dynamics of mechanisms by recomposing the components and their operations into an appropriately organized system. We will study this claim through the practice of combinational modeling in circadian clock research. In combinational modeling, experiments on model organisms and mathematical/computational models are combined with a new type of model—a synthetic model. We argue that the strategy of recomposition is more complicated than what Bechtel and Abrahamsen indicate. Moreover, synthetic (...) modeling as a kind of material recomposition strategy also points beyond the mechanistic paradigm. (shrink)

Default logic has been a very active research topic in artificial intelligence since the early 1980s, but has not received as much attention in the philosophical literature thus far. This paper shows one way in which the technical tools of artificial intelligence can be applied in contemporary epistemology by modeling a paradigmatic case of deep disagreement using default logic. In §1 model-building viewed as a kind of philosophical progress is briefly motivated, while §2 introduces the case of deep disagreement (...) we aim to model. On the heels of this, §3 defines our formal framework, viz., a refined Horty-style default logic. §4 then uses the framework to model deep disagreement, and finally §5 provides a critical discussion of the result. (shrink)