This chapter contains section titled: The Theory Theory The Theory Theory vs. Other Empiricist Alternatives Innate Theories and Starting‐state Nativism Phenomenological and Social Objections Universality, Uniformity, and Learning Theory Formation and Language.

Tarski’s conceptual analysis of the notion of logical consequence is one of the pinnacles of the process of defining the metamathematical foundations of mathematics in the tradition of his predecessors Euclid, Frege, Russell and Hilbert, and his contemporaries Carnap, Gödel, Gentzen and Turing. However, he also notes that in defining the concept of consequence “efforts were made to adhere to the common usage of the language of every day life.” This paper addresses the issue of what relationship Tarski’s analysis, and (...) Béziau’s further generalization of it in universal logic, have to reasoning in the everyday lives of ordinary people from the cognitive processes of children through to those of specialists in the empirical and deductive sciences. It surveys a selection of relevant research in a range of disciplines providing theoretical and empirical studies of human reasoning, discusses the value of adopting a universal logic perspective, answers the questions posed in the call for this special issue, and suggests some specific research challenges. (shrink)

In this article, the author focuses on Philip Kitcher's and Alvin Goldman's economic models of the social character of scientific knowledge production. After introducing some relevant methodological issues in the social sciences and characterizing Kitcher's and Goldman's models, the author goes on to show that special problems arise directly from the concept of an agent invoked in the models. The author argues that the two distinct concepts of agents, borrowed from economics and cognitive psychology, are inconsistent. Finally, the author discusses (...) some of the normative implications that arise from adopting economic concepts of agents in the study of science. (shrink)

This thesis offers a naturalist revision of Alain Badiou’s philosophy. This goal is pursued through an encounter of Badiou’s mathematical ontology and theory of truth with contemporary trends in philosophy of mathematics and philosophy of science. I take issue with Badiou’s inability to elucidate the link between the empirical and the ontological, and his residual reliance on a Heideggerian project of fundamental ontology, which undermines his own immanentist principles. I will argue for both a bottom-up naturalisation of Badiou’s philosophical approach (...) to mathematics and a top-down naturalisation. Articulating my particular understanding of what realism and naturalism should commit us to, I propose a creative fusion of Badiou’s attention to metamathematical results with a structural-informational metaphysics, proposing a ‘matherialism’ uniting the more daring speculative insights of the former with the naturalist and empiricist commitments motivating the latter. (shrink)

Part I Introduction The specific problem adressed in this thesis is: what is the rational use of theory and experiment in the process of scientific discovery, in theory and in the practice of drug research for Parkinson’s disease? The thesis aims to answer the following specific questions: what is: 1) the structure of a theory?; 2) the process of scientific reasoning?; 3) the route between theory and experiment? In the first part I further discuss issues about rationality in science as (...) introduction to part II, and I present an overview of my case-study of neuropharmacology, for which I interviewed researchers from the Groningen Pharmacy Department, as an introduction to part III. Part II Discovery In this part I discuss three theoretical models of scientific discovery according to studies in the fields of Logic, Cognition, and Computation. In those fields the structure of a theory is respectively explicated as: a set of sentences; a set of associated memory chunks; and as a computer program that can generate the observed data. Rationality in discovery is characterized by: finding axioms that imply observation sentences; heuristic search for a hypothesis, as part of problem solving, by applying memory chunks and production rules that represent skill; and finding the shortest program that generates the data, respectively. I further argue that reasoning in discovery includes logical fallacies, which are neccesary to introduce new hypotheses. I also argue that, while human subjects often make errors in hypothesis evaluation tasks from a logical perspective, these evaluations are rational given a probabilistic interpretation. Part III Neuropharmacology In this last part I discusses my case-study and a model of discovery in a practice of drug research for Parkinson’s disease. I discuss the dopamine theory of Parkinson’s disease and model its structure as a qualitative differential equation. Then I discuss the use and reasons for particular experiments to both test a drug and explore the function of the brain. I describe different kinds of problems in drug research leading to a discovery. Based on that description I distinguish three kinds of reasoning tasks in discovery, inference to: the best explanation, the best prediction and the best intervention. I further demonstrate how a part of reasoning in neuropharmacology can be computationally modeled as qualitative reasoning, and aided by a computer supported discovery system. (shrink)

This article raises issues of science, politics, economics and ethics. The first section presents the ontological transition from the first Copernican revolution to the second Copernican revolution in the global study of sustainability and the ethics of climate change. The second section describes the «Giddens’s paradox» and the Hilbertian program of the Earth System Science, that presuppose a paradigmatic challenge. Finally, the third section links this methodological challenge to the description of the «post-normal science» and the «transdisciplinarity chain» in a (...) post-Kuhnian epistemology.  . (shrink)