@incollection {1986, title = {The Feasibility of Modeling Hypothetical Reasoning by Formal Logics. Including an Overview of Adaptive Logics for Singular Fact Abduction}, booktitle = {Handbook of Model-Based Science}, year = {In Press}, publisher = {Springer}, author = {Gauderis, Tjerk}, editor = {Magnani, Lorenzo and Bertolotti, Tommaso} } @incollection {3178949, title = {Pauli{\textquoteright}s idea of the neutrino: how models in physics allow to revive old ideas for new purposes}, booktitle = {Model-based reasoning in science and technology : theoretical and cognitive issues}, year = {2013}, pages = {449-461}, publisher = {Springer}, abstract = {

Abstract Models have proven themselves to be the key catalyst of many new ideas in science. However, it is not yet fully clarified why models can fulfill such an important heuristic role. The two main reasons stated in the literature—the mental simulation of various scenarios and the wide cross-fertilization across various disciplines—seem to leave out one of the most obvious features of models: they are designed for a purpose. Therefore I investigated why, while the construction of models is a goal-oriented task with a predefined purpose, the use of models yields so many new ideas in science. This paper presents my conceptual analysis together with a detailed historical case study. The functional design of models forces scientists to explore vigorously older ideas to adapt them: as the lacunas in a functional model are also functional, scientists need to modify older ideas (that were formulated for different purposes) to fit the present functional gaps in their models. As such, they construct new ideas. The detailed historical case study exemplifies this by showing how Pauli’s original suggestion of the neutrino was, in fact, such an adaptation of Rutherford’s earlier idea of the neutron. The present analysis and case study suggest that functional adaptations are salient but often overlooked features of model based investigation.

}, author = {Gauderis, Tjerk}, editor = {Magnani, Lorenzo} } @incollection {1217131, title = {The symbolic model for algebra: functions and mechanisms}, booktitle = {Model-Based Reasoning in Science and Technology}, volume = {314}, year = {2010}, pages = {519{\textendash}532}, publisher = {Springer}, abstract = {

The symbolic mode of reasoning in algebra, as it emerged during the sixteenth century, can be considered as a form of model-based reasoning. In this paper we will discuss the functions and mechanisms of this model and show how the model relates to its arithmetical basis. We will argue that the symbolic model was made possible by the epistemic justification of the basic operations of algebra as practiced within the abbaco tradition. We will also show that this form of model-based reasoning facilitated the expansion of the number concept from Renaissance interpretations of number to the full notion of algebraic numbers.

}, isbn = {9783642152221}, url = {http://dx.doi.org/10.1007/978-3-642-15223-8\_29}, author = {Heeffer, Albrecht}, editor = {Magnani, Lorenzo and Carnielli, Walter A. and Pizzi, Claudio} } @incollection {D:vddiag, title = {A Diagrammatic Proof Search Procedure as Part of a Formal Approach to Problem Solving}, booktitle = {Model Based Reasoning in Science and Engineering. {C}ognitive Science, Epistemology, Logic}, year = {2006}, pages = {265{\textendash}284}, publisher = {King{\textquoteright}s College Publications}, abstract = {

This paper aims at describing a goal-directed and diagrammatic method for proof search. The method (and one of the logics obtained by it) is particularly interesting in the context of formal problem solving. A typical property is that it consists of attempts to justify so-called bottom boxes by means of premise elements (diagrammatic elements obtained from premises) and logical elements. Premises are not preprocessed, whence most premises lead to a variety of premise elements.

}, author = {Batens, Diderik}, editor = {Magnani, Lorenzo} } @incollection {402962, title = {A logical approach to the analysis of metaphors}, booktitle = {Logical and Computational Aspects of Model-Based Reasoning}, volume = {25}, year = {2002}, pages = {21{\textendash}37}, publisher = {Kluwer Academic}, address = {Dordrecht}, abstract = {

In this paper, I will present an adaptive logic that grasps the way we analyze metaphors. Metaphors are powerful tools to generate new scientific ideas. Therefore, it is important to have a good theory on what metaphors are and how they function. The first question we have to answer when we want to develop such a theory is obviously {\textacutedbl}what metaphors are{\textacutedbl}. Philosophy of language can offer some interesting ideas but most views do not allow for a cognitive function of metaphors. One of the sparse views that does allow for it is interactionism. The basic version, however, has some serious shortcomings that need solving when we want to use this theory. First of all the terminology is too vague. Furthermore, the description of the reasoning process we use when we analyze a metaphor, only works for very simple examples. The logic I will present, ALM, is based on a broadened version of this view. A logical approach of metaphors allows us to gain a profound insight in the way we analyze metaphors. The analysis of metaphors is a dynamical reasoning process. When we want to capture this process in a logical system, we need a logic that is capable of grasping that specific type of dynamics. An adaptive logic seems to be the best choice. Therefore, I shall present an adaptive logic that grasps the analysis of metaphors.

}, isbn = {1402007124}, author = {D{\textquoteright}Hanis, Isabel}, editor = {Magnani, Lorenzo and Nersessian, Nancy and Pizzi, Claudio} } @incollection {J:mbr, title = {Model-Based Reasoning in Creative Processes}, booktitle = {Model-Based Reasoning in Scientific Discovery}, year = {1999}, pages = {199{\textendash}217}, publisher = {Kluwer/Plenum}, address = {Dordrecht}, abstract = {

Combining a contextual approach to problem solving with results on some recently developed (non-standard) logics, I present in this paper a general frame for the methodological study of model-based reasoning in creative processes. I argue that model-based reasoning does not require that we turn away from logic. I also argue, however, that in order to better understand and evaluate creative processes that involve model-based reasoning, and in order to formulate guidelines for them, we urgently need to extend the existing variety of logics.

}, author = {Meheus, Joke}, editor = {Magnani, Lorenzo and Nersessian, Nancy and Thagard, Paul} }