: This paper offers a preliminary analysis of conceptual change between event concepts. It begins with a brief review of the major findings of cognitive studies on event knowledge. The script model proposed by Schank and Abelson was the first attempt to represent event knowledge. Subsequent cognitive studies indicated that event knowledge is organized in the form of dimensional organizations in which temporally successive actions are related causally. This paper proposes a frame representation to capture and outline the internal structure (...) of event concepts, in particular, their causal connections. The frame representation offers an effective method to analyze the relations between event concepts, and to expose the unique cognitive mechanisms behind conceptual change involved event concepts. Finally this paper shows that the frame representation of event concepts is instrumental to understanding an important historical episode of conceptual change in the context of nineteenth-century optics. (shrink)

Like belief revision, conceptual change has rational aspects. The paper discusses this for predicate change. We determine the meaning of predicates by a set of imaginable instances, i.e., conceptually consistent entities that fall under the predicate. Predicate change is then an alteration of which possible entities are instances of a concept. The recent exclusion of Pluto from the category of planets is an example of such a predicate change. In order to discuss predicate change, we define a monadic predicate logic (...) with three different kinds of lawful belief: analytic laws, which hold for all possible instances; doxastic laws, which hold for the most plausible instances; and typicality laws, which hold for typical instances. We introduce predicate changing operations that alter the analytic laws of the language and show that the expressive power is not affected by the predicate change. One can translate the new laws into old laws and vice versa. Moreover, we discuss rational restrictions of predicate change. These limit its possible influence on doxastic and typicality laws. Based on the results, we argue that predicate change can be quite conservative and sometimes even hardly recognisable. (shrink)

The paper suggests a way of modeling belief changes within the tradition of formal belief revision theories. The present model extends the scope of traditional proposals, such as AGM, so as to take care of “structural belief changes” – a type of radical shifts that is best illustrated with, but not limited to, instances of scientific discovery; we obtain AGM expansions and contractions as limiting cases. The representation strategy relies on a non-standard use of a semantic machinery. More precisely, the (...) model seeks to correlate knowledge states with interpretations of a given formal language L, in such a way that the epistemic state of an agent at a given time gives rise to a picture of how things could be, if there weren’t anything else to know. Interpretations of L proceed along supervaluational ideas; hence, the model as a whole can be seen as a particular application of supervaluational semantics to epistemic matters. (shrink)

It is shown that the probabilistic theories of coherence proposed up to now produce a number of counter-intuitive results. The last section provides some reasons for believing that no probabilistic measure will ever be able to adequately capture coherence. First, there can be no function whose arguments are nothing but tuples of probabilities, and which assigns different values to pairs of propositions {A, B} and {A, C} if A implies both B and C, or their negations, and if P(B)=P(C). But (...) such sets may indeed differ in their degree of coherence. Second, coherence is sensitive to explanatory relations between the propositions in question. Explanation, however, can hardly be captured solely in terms of probability. (shrink)

In the methodology of scientific research programs (MSRP) there are important features on the problem of prediction, especially regarding novel facts. In his approach, Imre Lakatos proposed three different levels on prediction: aim, process, and assessment. Chapter 5 pays attention to the characterization of prediction in the methodology of research programs. Thus, it takes into account several features: (1) its pragmatic characterization, (2) the logical perspective as a proposition, (3) the epistemological component, (4) its role in the appraisal of research (...) programs, and (5) its place as a value for scientific research. -/- The notion of “novel facts” is highly relevant in his conception, where several aspects are involved: the directions of novel facts, the different kinds of novelty, and the transition from six possible options of “novel facts” to four choices. Thereafter, the prediction of novel facts as the criterion of appraisal is considered. On the one hand, this requires analyzing the theoretical, empirical, and heuristic possibilities of appraisal; and, on the other, whether there is an overemphasis on the role of prediction in methodology of scientific research programs. As a consequence, there is an analysis of Lakatos’ criterion of appraisal in MSRP and economics. (shrink)

This article presents three experiments that examine the relation between order effects and frequency learning, with the following results. First, when frequencies of occurrence are presented as sequences of real events, base rates can be learned and used with a high degree of accuracy. However, conditional probabilities for multiple sequentially presented evidence items cannot be completely learned, due to the distortion of a recency order effect for actual decisions. Second, there is also a recency order effect for belief evaluations, which (...) cannot be eliminated even if base rates are used correctly. Third, base rates learned in one environment can be transferred to another environment, but the transfer soon diminishes due to learning in the new environment. However, belief evaluations are not transferred from one environment to another The existing models of frequency learning cannot explain the order effect for actual decisions because they do not consider sequential information. The existing models of belief updating can explain both types of order effects, but they do not have any mechanisms for frequency learning. To account for the complete spectrum of frequency learning and order effects, we outline our initial effort in developing a unified model that integrates frequency learning and order effects. (shrink)

This paper provides a computational characterization of coherence that applies to a wide range of philosophical problems and psychological phenomena. Maximizing coherence is a matter of maximizing satisfaction of a set of positive and negative constraints. After comparing five algorithms for maximizing coherence, we show how our characterization of coherence overcomes traditional philosophical objections about circularity and truth.

Explanatory contrastivists hold that we often explain phenomena of the form p rather than q. In this paper, I present a new, social‐epistemological model of contrastive explanation—accountabilism. Specifically, my view is inspired by social‐scientific research that treats explanations fundamentally as accounts; that is, communicative actions that restore one's social status when charged with questionable behaviour. After developing this model, I show how accountabilism provides a more comprehensive model of contrastive explanation than the causal models of contrastive explanation that are currently (...) en vogue. (shrink)

In this article I give a naturalistic-cum-formal analysis of therelation between beauty, empirical success, and truth. The analysis is based on the onehand on a hypothetical variant of the so-called `mere-exposure effect'' which has been more orless established in experimental psychology regarding exposure-affect relationshipsin general and aesthetic appreciation in particular (Zajonc 1968; Temme 1983; Bornstein 1989;Ye 2000). On the other hand it is based on the formal theory of truthlikeness andtruth approximation as presented in my From Instrumentalism to Constructive Realism (...) (2000).The analysis supports the findings of James McAllister in his beautifulBeauty and Revolution in Science (1996), by explaining and justifying them.First, scientists are essentially right in regarding aesthetic criteria useful for empiricalprogress and even for truth approximation, provided they conceive of them as less hard thanempirical criteria. Second, the aesthetic criteria of the time, the `aesthetic canon'', maywell be based on `aesthetic induction'' regarding nonempirical features of paradigms of successfultheories which scientists have come to appreciate as beautiful. Third, aestheticcriteria can play a crucial, schismatic role in scientific revolutions. Since they may well be wrong, they may, in the hands of aesthetic conservatives, retard empirical progress and hence truth approximation, but this does not happen in the hands of aesthetically flexible, `revolutionary'' scientists. We may find totallyopposite things beautiful: a simplemathematical principle as well as a series of unrepeatable complex contingencies. It is a matter of psychology.(Stephen Jay Gould, translated passage from (Kayzer 2000, 30)). (shrink)

Research into learners' ideas aboutscience suggests that school and collegestudents often hold alternative conceptionsabout `the atom'. This paper discusses whylearners acquire ideas about atoms which areincompatible with the modern scientificunderstanding. It is suggested that learners'alternative ideas derive – at least in part –from the way ideas about atoms are presented inthe school and college curriculum. Inparticular, it is argued that the atomicconcept met in science education is anincoherent hybrid of historical models, andthat this explains why learners commonlyattribute to atoms properties (...) (such as beingthe constituent particles of all substances, orof being indivisible and conserved inreactions) that more correctly belong to otherentities (such as molecules or sub-atomicparticles). Bachelard suggested that archaicscientific ideas act as `epistemologicalobstacles', and here it is argued thatanachronistic notions of the atom survive inthe chemistry curriculum. These conceptualfossils encourage learners to develop an`atomic ontology' (granting atoms `ontologicalpriority' in the molecular model of matter); tomake the `assumption of initial atomicity' whenconsidering chemical reactions; and to developan explanatory framework to rationalisechemical reactions which is based on thedesirability of full electron shells. Theseideas then act as impediments to thedevelopment of a modern chemical perspective onthe structure of matter, and an appreciation ofthe nature of chemical changes at the molecularlevel. (shrink)

This survey of major developments in North American philosophy of science begins with the mid-1960s consolidation of the disciplinary synthesis of internalist history and philosophy of science (HPS) as a response to criticisms of logical empiricism. These developments are grouped for discussion under the following headings: historical metamethodologies, scientific realisms, philosophies of the special sciences, revivals of empiricism, cognitivist naturalisms, social epistemologies, feminist theories of science, studies of experiment and the disunity of science, and studies of science as practice and (...) culture. A unifying theme of the survey is the relation between historical metamethodologists and scientific realists, which dominated philosophical work in the late 1970s. I argue that many of the alternative cognitive naturalisms, social epistemologies, and feminist theories that have been proposed can be understood as analogues to the differences between metamethodological theories of scientific rationality and realist accounts of successful reference to real causal processes. Recent work on experiment, scientific practice, and the culture of science may, however, challenge the underlying conception of the field according to which realism and historical rationalism (or their descendants) are the important alternatives available, and thus may take philosophy of science in new directions. (shrink)

There has been little research into the weak kindsof negating hypotheses. Hypotheses may be unfalsifiable. In this case it is impossible tofind a contradiction in some area of the conceptualsystems in which they are incorporated.Notwithstanding this fact, it is sometimes necessaryto construct ways of rejecting the unfalsifiablehypothesis at hand by resorting to some external forms of negation, external because wewant to avoid any arbitrary and subjectiveelimination, which would be rationally orepistemologically unjustified. I will consider akind of ``weak'''' (unfalsifiable) hypotheses that (...) arehard to negate and the ways for making it easy. Inthese cases the subject can ``rationally'''' decide towithdraw his hypotheses even in contexts where it is``impossible'''' to find ``explicit'''' contradictions: theuse of negation as failure (an interestingtechnique for negating hypotheses and accessing newones suggested by artificial intelligence) isilluminating. I plan to explore whether this kind ofnegation can be employed to model hypothesiswithdrawal in Poincaré''s conventionalism of theprinciples of physics and in Freudian analyticreasoning. (shrink)

Computational philosophy (CP) aims at investigating many important concepts and problems of the philosophical and epistemological tradition in a new way by taking advantage of information-theoretic, cognitive, and artificial intelligence methodologies. I maintain that the results of computational philosophy meet the classical requirements of some Peircian pragmatic ambitions. Indeed, more than a 100 years ago, the American philosopher C.S. Peirce, when working on logical and philosophical problems, suggested the concept of pragmatism(pragmaticism, in his own words) as a logical criterion to (...) analyze what words and concepts express through their practical meaning. Many words have been spent on creative processes and reasoning, especially in the case of scientific practices. In fact, many philosophers have usually offered a number of ways of construing hypotheses generation, but they aim at demonstrating that the activity of generating hypotheses is paradoxical, obscure, and thus not analyzable. Those descriptions are often so far from Peircian pragmatic prescription and so abstract to result completely unknowable and obscure. To dismiss this tendency and gain interesting insight about the so-called logic of scientific discovery we need to build constructive procedures, which could play a role in moving the problem-solving process forward by implementing them in some actual models. The computational turn gives us a new way to understand creative processes in a strictly pragmatic sense. In fact, by exploiting artificial intelligence and cognitive science tools, computational philosophy allows us to test concepts and ideas previously conceived only in abstract terms. It is in the perspective of these actual computational models that I find the central role of abduction in the explanation of creative reasoning in science. I maintain that the computational philosophy analysis of model-based and manipulative abduction and of external and epistemic mediators is important not only to delineate the actual practice of abduction, but also to further enhance the development of programs computationally adequate in rediscovering, or discovering for the first time, for example, scientific hypotheses or mathematical theorems. The last part of the paper is devoted to illustrating the problem of the extra-theoretical dimension of reasoning and discovery from the perspective of some mathematical cases derived from calculus and geometry. (shrink)

By the early part of the twentieth century, academia in the English-speaking world had stabilized (or ossified!) into a set of scientific and humanistic disciplines that still survives at the century’s end. The natural sciences have such disciplines as physics, chemistry, and biology, and the social sciences include economics, psychology, and sociology. These disciplines provide a convenient organizing principle for university departments and professional organizations, but they often bear little relation to cuttingedge research, which can concern topics that cut across (...) or occur at the boundaries of two or more of the established disciplines. When this happens, productive research and teaching must be interdisciplinary. Cognitive science is the interdisciplinary study of mind, embracing psychology, artificial intelligence, philosophy, neuroscience, linguistics, and anthropology. It is undoubtedly one of the major interdisciplinary successes of the twentieth century, with its own society, journal, and textbooks, and with more than sixty cognitive science programs established at universities in North American and Europe. This paper is an attempt to answer the question: What are the factors contributing to the success of the interdisciplinary field of cognitive science? My discussion is organized around the metaphor of the trading zone, a novel and fertile analogy that Gallison (1997) developed for his rich and detailed discussion of the practices of twentieth-century physics. To understand the diverse groups of December 1, 2006 experimenters and theoreticians, Gallison presents their interactions in terms of the trading zones described by anthropologists: Subcultures trade. Anthropologists have extensively studied how different groups, with radically different ways of dividing up the world and symbolically organizing its parts, can not only exchange goods but also depend essentially on those trades.. (shrink)

Deep appreciation of the relevance of emotion to epistemology requires a rich account of how emotional mental states such as happiness, sadness and desire interact with cognitive states such as belief and doubt. Analytic philosophy since Gottlob Frege and Bertrand Russell has assumed that such mental states are propositional attitudes, which are relations between a self and a proposition, an abstract entity constituting the meaning of a sentence. This chapter shows the explanatory defects of the doctrine of propositional attitudes, and (...) proposes instead that beliefs, desires, and emotions should be construed naturalistically using current understanding of brain mechanisms. Mental states are patterns of neural activity, not relations between dubious entities such as selves and propositions. From this perspective, it becomes easy to see how cognition and emotion are intertwined, and hence how emotions can be integral to epistemology. I begin by reviewing some of the ways in which emotions are relevant to epistemology: as frequent contributors to the growth of knowledge, as sometime impediments to knowledge acquisition, and as components of knowledge about persons and morality. I then argue that propositional attitudes do not exist, because the selves and the propositions that they purportedly relate do not exist. Thus the doctrine of propositional attitudes is as useless for epistemology as it is for explaining human action. I argue for an alternative construal of mental states as patterns of neural activity, and July 23, 2007 describe how it is possible to give a theoretically rich and empirically supported account of the neurophysiological interconnections of cognition and emotion. Finally, I discuss the epistemological significance of this naturalistic, materialist reconstrual of cognitions and emotions. (shrink)

Recent theorizing about the nature of the cognitive impairment in autism suggests that autistic individuals display abnormally weak central coherence, the capacity to integrate information in order to make sense of one’s environment. Our article shows the relevance of computational models of coherence to the understanding of weak central coherence. Using a theory of coherence as constraint satisfaction, we show how weak coherence can be simulated ina a connectionist network that has unusually high inhibition compared to excitation. This connectionist model (...) simulates autistic behaviour on both the false belief task and the homograph task. (shrink)

This thesis studies the role of conceptual content in inference and reasoning. The first two chapters offer a theoretical and historical overview of the relation between inference and meaning in philosophy and psychology. In particular, a critical analysis of the formality thesis, i.e., the idea that rational inference is a rule-based and topic-neutral mechanism, is advanced. The origins of this idea in logic and its influence in philosophy and cognitive psychology are discussed. Chapter 3 consists of an analysis of the (...) relationship between inference and representation. It is argued that inference has to be studied from a pluralistic per- spective due to its dependence on different formats of representing information. The following four chapters apply conceptual spaces, a formal theory of concepts within cognitive semantics, to three concept-based inference-types. First, an explication of Sellars notion of material inference is advanced. Later, the model is extended to account for nonmonotonic inference by studying the role expectations in reasoning. Finally, a conceptual space-model of category-based induction is presented. This model predicts most of the empirical properties of this psychological phenomenon and subsumes some of the previous theories in psychology. It is stated that the explanatory fruitfulness of this new approach is evidence for the failure of the formality thesis and calls for a unified model of rational inference that puts semantics at center stage. The last chapter of the thesis discusses how inference and concepts interact in scientific reasoning, which makes constant use of hybrid symbolic structures for representing conceptual information. Stephen Toulmin’s notions of method of representation and inferential technique are developed and applied in a case study about the emergence of the notion of instantaneous speed during the passage from geometrical physics to analytical mechanics. It is claimed that this analysis provides support to the pluralistic perspective for theorizing about reasoning. (shrink)

Debates about evolution and creation inevitably raise philosophical issues about the nature of scientific knowledge. What is a theory? What is an explanation? How is science different from non- science? How should theories be evaluated? Does science achieve truth? The aim of this chapter is to give a concise and accessible introduction to the philosophy of science, focusing on questions relevant to understanding evolution by natural selection, creation, and intelligent design. For the questions just listed, I state what I think (...) is the best available answer and show how it applies to debates about evolution and creationism. I also indicate alternative answers that are preferred by other philosophers. I hope that the result will be useful for science educators and anyone else involved in controversies about evolution and creation. (shrink)

Here are some of the most important discoveries in the history of medicine: blood circulation (1620s), vaccination, (1790s), anesthesia (1840s), germ theory (1860s), X- rays (1895), vitamins (early 1900s), antibiotics (1920s-1930s), insulin (1920s), and oncogenes (1970s). This list is highly varied, as it includes basic medical knowledge such has Harvey’s account of how the heart pumps blood, hypotheses about the causes of disease such as the germ theory, ideas about the treatments of diseases such as antibiotics, and medical instruments such (...) as X-ray machines. The philosophy of medicine should be able to contribute to understanding of the nature of discoveries such as these. The great originators of the field of philosophy of science were all concerned with the nature of scientific discovery, including Francis Bacon (1960), William Whewell (1967), John Stuart Mill (1974), and Charles Peirce (1931-1958). The rise of logical positivism in the 1930s pushed discovery off the philosophical agenda, but the topic was revived through the work of philosophers such as Norwood Russell Hanson (1958), Thomas Nickles (1980), Lindley Darden (1991, 2006), and Nancy Nersessian (1984). Scientific discovery has also become an object of investigations for researchers in the fields of cognitive psychology and artificial intelligence, as seen in the work of Herbert Simon, Pat Langley, and others (Langley et al., 1987; Klahr, 2000). Today, scientific September 14, 2009 discovery is an interdisciplinary topic at the intersection of the philosophy, history, and psychology of science. The aim of this chapter is to identify patterns of discovery that illuminate some of the most important developments in the history of medicine. I have used a variety of sources to identify forty great medical discoveries (Adler, 2004; Friedman and Friedland, 1998; Science Channel, 2006; Strauss and Strauss, 2006).. (shrink)

The models used in social simulation to date have mostly been very simplistic cognitively, with little attention paid to the details of individual cognition. This work proposes a more cognitively realistic approach to social simulation. It begins with a model created by Gilbert (1997) for capturing the growth of academic science. Gilbert’s model, which was equation-based, is replaced here by an agent-based model, with the cognitive architecture CLARION providing greater cognitive realism. Using this cognitive agent model, results comparable to previous (...) simulations and to human data are obtained. It is found that while different cognitive settings may affect the aggregate number of scientific articles produced, they do not generally lead to different distributions of number of articles per author. The paper concludes with a discussion of the correspondence between our model and the constructivist view of academic science. It is argued that using more cognitively realistic models in simulations may lead to novel insights. (shrink)

This paper discusses Theo Kuipers' account of beauty and truth. It challenges Kuipers' psychological account of how scientists come to appreciate beautiful theories, as well as his attempt to justify the use of aesthetic criteria on the basis of a "meta-induction." I propose an alternative psychological/philosophical account based on emotional coherence.

Barnes, A. and P. Thagard Empathy and analogy. Dialogue: Canadian Philosophical Review, 36: 705-720. HTML Croft, D., & Thagard, P.. Dynamic imagery: A computational model of motion and visual analogy. In L. Magnani and N. Nersessian, Model-based reasoning: Science, technology, values. New York: Kluwer/Plenum, 259-274. PDF only. HTML description of program and code for DIVA.

Over the past years, a number of probabilistic measures of coherence have been proposed. As shown in the paper, however, many of them do not conform to the intuitition that equivalent testimonies are highly coherent, regardless of their prior probability.

This work contrasts Giovanni Sartor’s view of inferential semantics of legal concepts with a probabilistic model of theory formation. The work further explores possibilities of implementing Kemp’s probabilistic model of theory formation in the context of mapping legal concepts between two individual legal systems. For implementing the legal concept mapping, we propose a cross-categorization approach that combines three mathematical models: the Bayesian Model of Generalization, the probabilistic model of theory formation, i.e., the Infinite Relational Model first introduced by Kemp et (...) al. and its extended model, i.e., the normal-IRM proposed by Herlau et al.. We apply our cross-categorization approach to datasets where legal concepts related to educational systems are respectively defined by the Japanese- and the Danish authorities according to the International Standard Classification of Education. The main contribution of this work is the proposal of a conceptual framework of the cross-categorization approach that, inspired by Sartor, attempts to explain reasoner’s inferential mechanisms. (shrink)

Computer science only became established as a field in the 1950s, growing out of theoretical and practical research begun in the previous two decades. The field has exhibited immense creativity, ranging from innovative hardware such as the early mainframes to software breakthroughs such as programming languages and the Internet. Martin Gardner worried that "it would be a sad day if human beings, adjusting to the Computer Revolution, became so intellectually lazy that they lost their power of creative thinking" (Gardner, 1978, (...) p. vi-viii). On the contrary, computers and the theory of computation have provided great opportunities for creative work. This chapter examines several key aspects of creativity in computer science, beginning with the question of how problems arise in computer science. We then discuss the use of analogies in solving key problems in the history of computer science. Our discussion in these sections is based on historical examples, but the following sections discuss the nature of creativity using information from a contemporary source, a set of interviews with practicing computer scientists collected by the Association of Computing Machinery’s on-line student magazine, Crossroads. We then provide a general comparison of creativity in computer science and in the natural sciences. (shrink)

There is a demand to nurture scientific creativity in science education. This paper proposes that the relevant conceptual infrastructure with which to teach scientific creativity is often already included in philosophy of science courses, even those that do not cover scientific creativity explicitly. More precisely, it is shown how paradigm theory can serve as a framework with which to introduce the differences between combinational, exploratory, and transformational creativity in science. Moreover, the types of components given in Kuhn’s disciplinary matrix are (...) argued to indicate a further subdivision within transformational creativity that makes explicit that this most radical type of creativity that aims to go beyond and thus to transform the current paradigm can take many different directions. More generally, it is argued that there are several synergies between the topic of scientific creativity and paradigm theory that can be utilized in most philosophy of science courses at relative ease. Doing so should promote the understanding of scientific creativity among students, provide another way to signify the relevance of paradigm theory, and more strategically be a way of reinforcing the place of philosophy of science in science education. (shrink)

This paper argues that, as all available accounts of how scientific and non-scientific goals might be distinguished rely upon distinctions as much in need of explication as the notion of scientific goals itself, naturalized accounts of science should reject the notion that there are characteristically scientific goals for a given time and place and instead countenance only the goals which happen to be had by individual scientists or their communities. This argument and the recommendation that follows from it are illustrated (...) by reference to Watson and Crick's discovery of the structure of DNA. (shrink)

Analizamos las transformaciones de la noción de "horizonte" en la modernidad a través de sus usos en obras científicas del período 1440-1624; en particular, en el marco de la discusión que tuvo lugar a propósito de la disputa entre geocentristas y heliocentristas con relación al argumento ptolemaico que establecía que el comportamiento del horizonte probaba la posición central de la Tierra. Señalamos cómo el concepto de "horizonte" es representativo de otros conceptos fundamentales que caracterizan a los sistemas cosmológicos en pugna, (...) de los respectivos sentidos de realidad y del correspondiente carácter de la observación. Mostramos cómo el estudio de los cambios conceptuales históricamente operados en la noción de "horizonte" implica una nueva aproximación a la denominada revolución científica. We analyze the transformations of the notion of horizon in modernity through the different uses that it had in scientific works, written between 1440 and 1624, in which there was discussion of the Ptolemaic argument for the view that the behavior of the horizon proves the centrality of the Earth. We show how the concept of horizon represents other fundamental concepts, which characterize the cosmological systems in dispute and their respective senses of reality and observation. We maintain that the study of the conceptual changes that took place historically in the notion of horizon imply taking a new approach to the so-called Scientific Revolution. (shrink)

The ‘triumph of the anti-phlogistians’ is a familiar story to the historians and philosophers of science who characterize the Chemical Revolution as a broad conceptual shift. The apparent “incommensurability” of the paradigms across the revolutionary divide has caused much anxiety. Chemists could identify phlogiston and oxygen, however, only with different sets of instrumental practices, theoretical schemes, and philosophical commitments. In addition, the substantive counterpart to phlogiston in the new chemistry was not oxygen, but caloric. By focusing on the changing visions (...) of chemical body across the revolutionary divide with a more sensitive probe into the historical actors’ material manipulations and linguistic usage, we can historicize their laboratory realities and philosophical agenda. An archeology of chemical bodies that configures the fragile stability of the material worlds chemists created in succession promises a philosophical horizon that would recognize our hybrid (natural–artificial) environment as an evolving investigative object of science. (shrink)

Philosophers of science today by and large reject the cataclysmic and irrational interpretation of the scientific enterprise claimed by Kuhn. Many computational models have been implemented to rationally study the conceptual change in science. In this recent tradition a key role is played by the concept of abduction as a mechanism by which new explanatory hypotheses are introduced. Nevertheless some problems in describing the most interesting abductive issues rise from the classical computational approach. It describes a cognitive process (and so (...) abduction) by the manipulation of internal symbolic representations of external world. This view assumes a discrete set of representations fixed in discrete time jumps, and cannot adequately account for the issue of anticipation and causation of a new hypothesis. An integration of the traditional computational view with some ideas developed inside the so-called dynamical approach can suggest some important insights. The concept of attractor is very significant. It permits a description of the abductive generation of new hypotheses in terms of a catastrophic rearrangement of the parameters responsible for the behavior of the system. (shrink)

What I call theoretical abduction (sentential and model-based) certainly illustrates much of what is important in abductive reasoning, especially the objective of selecting and creating a set of hypotheses that are able to dispense good (preferred) explanations of data, but fails to account for many cases of explanations occurring in science or in everyday reasoning when the exploitation of the environment is crucial. The concept of manipulative abduction is devoted to capture the role of action in many interesting situations: action (...) provides otherwise unavailable information that enables the agent to solve problems by starting and performing a suitable abductive process of generation or selection of hypotheses. Many external things, usually inert from the epistemological point of view, can be transformed into what I call epistemic mediators, which are illustrated in the last part of the paper, together with an analysis of the related notion of external representation . Finally, some examples of computational programs that simulate geometrical reasoning are illustrated. The computational embodiment generates a kind of squared epistemic mediator: geometrical construction, as an example of epistemic mediator, is further mediated. (shrink)

Many important concepts of the calculus are difficult to grasp, and they may appear epistemologically unjustified. For example, how does a real function appear in “small” neighborhoods of its points? How does it appear at infinity? Diagrams allow us to overcome the difficulty in constructing representations of mathematical critical situations and objects. For example, they actually reveal the behavior of a real function not “close to” a point (as in the standard limit theory) but “in” the point. We are interested (...) in our research in the diagrams which play an optical role –microscopes and “microscopes within microscopes”, telescopes, windows, a mirror role (to externalize rough mental models), and an unveiling role (to help create new and interesting mathematical concepts, theories, and structures). In this paper we describe some examples of optical diagrams as a particular kind of epistemic mediator able to perform the explanatory abductive task of providing a better understanding of the calculus, through a non-standard model of analysis. We also maintain they can be used in many other different epistemological and cognitive situations. (shrink)

The innovation systems approach has swiftly spread out worldwide in the last three decades and stood as an important framework for policy-making in the fields of science, technology, and innovation. At the same time, there have been serious and untreated concerns in the literature about the theoretical soundness of this approach. Our discussion in this paper is based on the belief that a detailed analysis on epistemological foundations of the approach could shed a judgmental light on the aforementioned concerns. To (...) provide that analysis, we reconstructed and studied the nature and evolution of innovation systems approach as a case of conceptual revolution against the more established traditions in economics of innovation. Our analyses show that the rise of the systemic view of innovation include radical changes in conceptual structures pertaining to orthodox view of innovation. These developments also go so far as to include significant shifts in epistemological foundations of the old paradigm. These later shifts provide us with an epistemological base from which we can shelter the innovation systems approach from the hard criticisms rooted in a quasi-positivist point of view. That epistemological base also shows the path for the future development of the approach towards more robustness and precision. (shrink)