Knowledge of residual perturbations in Uranus's orbit led to Neptune's discovery in 1846 rather than the refutation of Newton's law of gravitation. Karl Popper asserts that this case is untypical of science and that the law was at least prima facie falsified. I argue that these assertions are the product of a false, a priori methodological position, 'Weak Popperian Falsificationism' (WPF), and that on the evidence the law was not, and was not considered, prima facie false. Many of Popper's commentators (...) presuppose WPF and their views on this case and its implications for scientific rationality and method are similarly unwarranted or defective. (shrink)

The first part of this paper shows that Qualitative Comparative Analysis (QCA)--also in its most recent forms as presented in Ragin (2000, 2008)--, does not correctly analyze data generated by causal chains, which, after all, are very common among causal processes in the social sciences. The incorrect modeling of data originating from chains essentially stems from QCA’s reliance on Quine-McCluskey optimization to eliminate redundancies from sufficient and necessary conditions. Baumgartner (2009a,b) has introduced a Boolean methodology, termed Coincidence Analysis (CNA), that (...) is related to QCA, yet, contrary to the latter, does not eliminate redundancies by means of Quine-McCluskey optimization. The second part of the paper applies CNA to chain-generated data. It will turn out that CNA successfully detects causal chains in small-N data. (shrink)

Whereas an inference (deductive as well as inductive) is usually viewed as being valid in virtue of its argument form, the present paper argues that scientific reasoning is material inference, i.e., justified in virtue of its content. A material inference is licensed by the empirical content embodied in the concepts contained in the premises and conclusion. Understanding scientific reasoning as material inference has the advantage of combining different aspects of scientific reasoning, such as confirmation, discovery, and explanation. This approach explains (...) why these different aspects (including discovery) can be rational without conforming to formal schemes, and why scientific reasoning is local, i.e., justified only in certain domains and contingent on particular empirical facts. The notion of material inference also fruitfully interacts with accounts of conceptual change and psychological theories of concepts. (shrink)

Review essay of The Philosophy of Experimental Biology by Marcel Weber (Cambridge University Press, 2005).

It is usual when writing on research methodology in dissertations and thesis work within Software Engineering to refer to Empirical Methods, Grounded Theory and Action Research. Analysis of Constructive Research Methods which are fundamental for all knowledge production and especially for concept formation, modeling and the use of artifacts is seldom given, so the relevant first-hand knowledge is missing. This article argues for introducing of the analysis of Constructive Research Methods, as crucial for understanding of research process and knowledge production. (...) The paper provides characterization of the Constructive Research Method and its relations to Action Research and Grounded Theory. Illustrative example of Blue Brain Project is presented. Finally, foundations of Constructive Research are analyzed within the framework of Info-Computationalism which provides models of knowledge construction by information processing in a cognizing agent. (shrink)

Review of: Isabelle Stengers (2010), Cosmopolitics I, trans. Robert Bononno (Posthumanities, 9) (Minneapolis/London: University of Minnesota Press).

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)

This volume is based on the papers presented at the international conference Model-Based Reasoning in Science and Technology (MBR09_BRAZIL), held at the University of Campinas (UNICAMP), Campinas, Brazil, December 2009. The presentations given at the conference explored how scientific cognition, but several other kinds as well, use models, abduction, and explanatory reasoning to produce important or creative changes in theories and concepts. Some speakers addressed the problem of model-based reasoning in technology, and stressed the issue of science and technological innovation. (...) The various contributions of the book are written by interdisciplinary researchers who are active in the area of creative reasoning in logic, science, and technology: the most recent results and achievements about the topics above are illustrated in detail in the papers. The book is divided in three parts, which cover the following main areas: part I, abduction, problem solving, and practical reasoning; part II: formal and computational aspects of model based reasoning; part III, models, mental models, representations. (shrink)

Academic inquiry has two basic inter-related aims. One is to explore intellectually aspects of our world of intrinsic interest and value, for its own sake, and to encourage non-academics to participate in such exploration, thus improving our knowledge and understanding. The other is, by intellectual means, to help humanity solve its problems of living, so that a more peaceful, just, democratic and environmentally enlightened world may be attained. Both are at present betrayed.

Cosmological speculation about the ultimate nature of the universe, being necessary for science to be possible at all, must be regarded as a part of scientific knowledge itself, however epistemologically unsound it may be in other respects. The best such speculation available is that the universe is comprehensible in some way or other and, more specifically, in the light of the immense apparent success of modern natural science, that it is physically comprehensible. But both these speculations may be false; in (...) order to take this possibility into account, we need to adopt an hierarchy of increasingly contentless cosmological conjectures until we arrive at the conjecture that the universe is such that it is possible for us to acquire some knowledge of something, a conjecture which we are justified in accepting as knowledge since doing so cannot harm the pursuit of knowledge in any circumstances whatsoever. As a result of adopting such an hierarchy of increasingly contentless cosmological conjectures in this way, we maximize our chances of adopting conjectures that promote the growth of knowledge, and minimize our chances of taking some cosmological assumption for granted that is false and impedes the growth of knowledge. The hope is that as we increase our knowledge about the world we improve (lower level) cosmological assumptions implicit in our methods, and thus in turn improve our methods. As a result of improving our knowledge we improve our knowledge about how to improve knowledge. Science adapts its own nature to what it learns about the nature of the universe, thus increasing its capacity to make progress in knowledge about the world. This aim-oriented empiricist conception of science solves outstanding problems in the philosophy of science such as the problems of induction, simplicity and verisimilitude. (shrink)

In this article, I compare two varieties of abduction as reconstructive models for analysing discovery. The first is 'Hansonian abduction', which is based on N. R. Hanson's formulations of abduction. The other is 'Harmanian abduction', the Inference to the Best Explanation (IBE) model, formulated especially by Gilbert Harman. Peter Lipton has analysed processes of discovery on the basis of his developed form of Harmanian abduction. I argue that Hansonian abduction would, however, be a more apt model for this purpose. As (...) an example, I reconstruct, in a Hansonian manner, Ignaz Semmelweis's research on childbed fever and compare it to the IBE reconstruction of Lipton. I argue that Hansonian abduction is in accordance with Lipton's aim of taking into account the distinction between actual and potential explanations on the one hand, and between likely and lovely explanations on the other. I maintain that a developed version of Hansonian abduction combined with loveliness gives an important, new conceptual means for analysing processes of discovery. (shrink)

There are various ``classical'' arguments against abduction as a logic of discovery,especially that (1) abduction is too weak a mode of inference to be of any use, and (2) in basic formulation of abduction the hypothesisis already presupposed to be known, so it is not the way hypotheses are discovered in the first place. In this paper I argue, by bringing forth the idea of strategies,that these counter-arguments are weaker than may appear. The concept of strategies suggests, inter alia, that (...) many inferential moves are taken into account at the same time. This is especially important in abductive reasoning, which is basically a very weak mode of inference. The importance of strategic thinking can already be seen in Charles S.Peirce's early treatments of the topic, and N.R.Hanson's later writings on abduction although they did not use the concept of``strategies.'' On the whole, I am arguing that the focus should be more on methodological processes, and not only on validity considerations, which have dominated the discussion about abduction. (shrink)

I examine the role of inference from experiment in theory building. What are the options open to the scientific community when faced with an experimental result that appears to be in conflict with accepted theory? I distinguish, in Laudan’s (1977), Nickels’s (1981), and Franklin’s (1993) sense, between the context of pursuit and the context of justification of a scientific theory. Making this distinction allows for a productive middle position between epistemic realism and constructivism. The decision to pursue a new or (...) a revised theory in response to the new evidence may not be fully rationally determined. Nonetheless, it is possible to distinguish the question of whether there is reason to pursue a theory from the question of whether that theory, once it has been pursued over time, solves a problem of interest to science. I argue that, in this context, there is a solid way to distinguish between the contexts of pursuit and of justification, on the basis of a theory’s evidential support and problem-solving ability. (shrink)

In this paper I discuss Newton's first optical paper. My aim is to examine the type of argument which Newton uses in order to convince his readers of the truth of his theory of colors. My claim is that this argument is an induction by elimination, and that the Newtonian method of justification is a kind of generative justification, a term due to T. Nickles. To achieve my aim I analyze in some detail the arguments in Newton's first optical paper, (...) relating the paper with Newton's other writings in optics, and especially his early correspondence in defence of his theory of colors. (shrink)

References to Kant's so-called Copernicanism or Copernican turn are often put in very general terms. It is commonly thought that Kant makes the Copernican analogy solely in order to point out the fact as such of a paradigm shift in philosophy. This is too historical an interpretation of the analogy. It leaves unexplained both Kant's and Copernicus' reasons for advancing their respective hypotheses, which brought about major changes in the conceptual schemes of philosophy and astronomy. My contention is that something (...) much more specific, systematic is at issue, which contrary to received understanding makes Kant's analogy in fact particularly apt. (shrink)

In psychiatry, pharmacological drugs play an important experimental role in attempts to identify the neurobiological causes of mental disorders. Besides being developed in applied contexts as potential treatments for patients with mental disorders, pharmacological drugs play a crucial role in research contexts as experimental instruments that facilitate the formulation and revision of neurobiological theories of psychopathology. This paper examines the various epistemic functions that pharmacological drugs serve in the discovery, refinement, testing, and elaboration of neurobiological theories of mental disorders. I (...) articulate this thesis with reference to the history of antipsychotic drugs and the evolution of the dopamine hypothesis of schizophrenia in the second half of the twentieth century. I argue that interventions with psychiatric patients through the medium of antipsychotic drugs provide researchers with information and evidence about the neurobiological causes of schizophrenia. This analysis highlights the importance of pharmacological drugs as research tools in the generation of psychiatric knowledge and the dynamic relationship between practical and theoretical contexts in psychiatry. (shrink)