@incollection {provijn2014bloody, title = {Bloody analogical reasoning}, booktitle = {Logic, Reasoning, and Rationality}, year = {2014}, pages = {217{\textendash}232}, publisher = {Springer}, abstract = {

In this paper I will study some of William Harvey’s applications of analogies in the Prelectiones Anatomiae Universalis and the Exercitatio anatomica de motu cordis et sanguinis in animalibus. I will show that Harvey applied analogies in many different ways and that some contributed to the discovery of the characteristic ‘action’ of the heart and pulse and even to the discovery of the blood circulation. The discovery process will be approached as a problem solving process as described in Batens’ contextual model. The focus on constraints allows to see Harvey both as a modern because of his extensive use of experimental results and as strongly influenced by an Aristotelian ‘natural philosophy interpretation’ of anatomy and physiology as, for instance, propagated by Fabricius of Aquapendente.

}, doi = {10.1007/978-94-017-9011-6_11}, author = {Provijn, Dagmar}, editor = {Weber, Erik and Wouters, Dietlinde and Meheus, Joke} } @incollection {5673678, title = {Data-driven induction in scientific discovery: a critical assessment based on Kepler{\textquoteright}s discoveries}, booktitle = {Logic, reasoning, and rationality}, year = {2014}, pages = {59{\textendash}76}, publisher = {Springer}, abstract = {

Motivated by the renewed interest in knowledge discovery from data (KDD) by the artificial intelligence community, this paper provides a critical assessment of the model of data-driven induction for scientific discovery. The most influential research program using this model is developed by the BACON team. Two of the main claims by this research program, the descriptive and constructive power of data-driven induction, are evaluated by means of two historical cases studies: the discovery of the sine law of refraction in optics and Kepler{\textquoteright}s third law of planetary motion. I will provide evidence that the data used by the BACON program{\textendash}-despite the claims being made{\textendash}-does not correspond with the historical data available to Kepler and his contemporaries. Secondly, it is shown that for the two cases the method by which the general law was arrived at did not involve data-driven induction. Finally, the value of the data-driven induction as a general model for scientific discovery is being questioned.

}, isbn = {9789401790109}, doi = {http://dx.doi.org/10.1007/978-94-017-9011-6\_4}, author = {Heeffer, Albrecht}, editor = {Weber, Erik and Wouters, Dietlinde and Meheus, Joke} } @incollection {4443651, title = {Explaining capacities: Assessing the explanatory power of models in the cognitive sciences}, booktitle = {Logic, Reasoning, and Rationality}, year = {2014}, pages = {45-57}, publisher = {Springer}, author = {Gervais, Raoul}, editor = {Weber, Erik and Wouters, Dietlinde and Meheus, Joke} } @incollection {Wieland2014, title = {Internalism Does Entail Scepticism}, booktitle = {Logic, Reasoning, and Rationality}, series = {Logic, Argumentation \& Reasoning}, volume = {5}, year = {2014}, pages = {247-260}, publisher = {Springer Netherlands}, abstract = {

Let Internalism be the view that our inferences are justified depending on whether we have knowledge of the logical rules on which they are based, and Scepticism the view that none of our inferences are justified. Boghossian has shown that Internalism entails Scepticism, and Philie has attempted to block the entailment by invoking an assumption on rationality. In this contribution, I enforce the entailment claim and argue that Philie’s solution misses the target: Internalism does entail Scepticism.

}, keywords = {Internalism, Knowledge, Regress, Rule, Scepticism}, isbn = {978-94-017-9010-9}, doi = {10.1007/978-94-017-9011-6_13}, author = {Wieland, Jan Willem}, editor = {Weber, Erik and Wouters, Dietlinde and Meheus, Joke} }