Analogical Reasoning and Modeling in the Sciences (original) (raw)

In Defense of Analogical Reasoning

2008

I offer a defense of analogical accounts of scientific models by meeting certain logical objections to the legitimacy of analogical reasoning. I examine an argument by Joseph Agassi that purports to show that all putative cases of analogical inference succumb to the following dilemma: either (1) the reasoning remains hopelessly vague and thus establishes no conclusion, or (2) can be analyzed into a logically preferable non-analogical form. In rebuttal, I offer a class of scientific models for which (a) there is no satisfactory non-analogical analysis, and (b) we can gain sufficient clarity for the legitimacy of the inference to be assessed. This result constitutes an existence proof for a class of analogical models that escape Agassi's dilemma.

Remarks on the Meaning of Analogical Relations

Proceedings of the 3d Conference on Artificial General Intelligence (AGI-10), 2010

Analogical reasoning plays an important role in the context of higher cognitive abilities of humans. Analogies can be used not only to explain reasoning abilities of humans, but also to explain learning from sparse data, creative problem solving, abstractions of concrete situations, and recognition of formerly unseen situations, just to mention some examples. Research in AI and cognitive science has been proposing several different models of analogy making. Nevertheless, no approach for a model theoretic semantics of analogy making is currently available. This paper gives an analysis of the meaning (the semantics) of analogical relations that are computed by the analogy engine HDTP (Heuristic-Driven Theory Projection).

The formal structure(s) of analogical inference

Recently, Dardashti, Hartmann, Thébault, and Winsberg (2019) proposed a Bayesian model for establishing Hawking radiation by analogical inference. In this paper we investigate whether their model would work as a general model for analogical inference. We study how it performs when varying the believed degree of similarity between the source and the target system. We show that there are circumstances in which the degree of confirmation for the hypothesis about the target system obtained by collecting evidence from the source system goes down when increasing the believed degree of similarity between the two systems. We then develop an alternative model in which the direction of the variation of the degree of confirmation always coincides with the direction of the believed degree of similarity. Finally, we argue that the two models capture different types of analogical inference. Citation information: Gebharter, A., & Osimani, B. (forthcoming). The formal structure(s) of analogical inference. Erkenntnis.

Analogical Reasoning as an Inference Scheme

Dialogue, 2021

Analogy plays an important role in science as well as in non-scientific domains such as taxonomy or learning. We make explicit the difference and complementarity between the concept of analogical statement, which merely states that two objects have a relevant similarity, and the concept of analogical inference, which relies on the former in order to draw a conclusion from some premises. For the first, we show that it is not possible to give an absolute definition of what it means for two objects to be analogous; a relative definition of analogy is introduced, only relevant from some point of view. For the second, we argue that it is necessary to introduce a background over-hypothesis relating two sets of properties; the belief strength of the conclusion is then directly related to the belief strength of the over-hypothesis. Moreover, we assert the syntactical identity between analogical inference and single case induction despite important pragmatic differences.

An Approach to the Semantics of Analogical Relations1

2007

Whereas approaches for deductive and inductive reasoning are well-examined for decades, analogical reasoning seems to be a hard problem for machine intelligence. Although several models for computing analogies have been proposed, there is no uncontroversial theory of the semantics of analogies. In this paper, we will investigate semantic issues of analogical relations, in particular, we will specify a model theory of analogical transfers. The presented approach is based on Heuristic-Driven Theory Projection (HDTP) a framework that computes an analogical relation between logical theories describing a source and a target domain. HDTP establishes the analogy by an abstraction process in which formulas from both domains are generalized creating a theory that syntactically subsumes the original theories. We will show that this syntactic process can be given a sensible interpretation on the semantic level. In particular, given models of the source and the target domains, we will examine t...

Analogy as categorization: a support for model-based reasoning

in L. Magnani e C. Casadio (eds.), Model-Based Reasoning in Science and Technology – Logical, Epistemological and Cognitive Issues, Series: Studies in Applied Philosophy, Epistemology and Rational Ethics, Vol. 27, Springer International Publishing AG, Cham, 2016

Generally speaking, model-based reasoning refers to every reasoning that involves model of reality or physical world, and it is especially involved in scientific discovery. Analogy is a cognitive process involved in scientific discovery as well as in everyday thinking. I suggest to consider analogy as a type of model-based reasoning and in relation with models. Analogy requires models in order to connect a source situation and a target situation. A model in an analogy is required to establish salient properties and, mostly, relations that allow transfer of knowledge from the source domain to the target domain. In another sense, analogy is the model itself, or better, analogy provides the elements of model of reality that enable the processes of scientific discovery or knowledge increase. My suggestion is that some insight on how an analogy is a model and is connected to model-based reasoning is provided by recently proposed theories about analogy as a cat-egorization phenomenon. Seeing analogy as a categorization phenomenon is a fruitful attempt to solve the problem of feature relevance in analogies, especially in the case of conceptual innovation and knowledge increase in scientific domain.

The Cumulative Force of Analogies

Logic and Logical Philosophy

In this paper I will argue that most objections to deductive analyses of a priori analogies are incorrect, often involve basic misinterpretations of what the deductive reconstruction of those arguments are saying, and sometimes also betray a confusion about what part of the reasoning corresponds to the analogical inference. In particular, I will be focusing on a raft of objections made by Juthe in [2015] and subject his alternative views to criticism. I will then argue that Juthe does implicitly have a good argument against deductivism: adding further analogues seems to have a cumulative force that they would not have on a deductivist analysis. This is so not only in ordinary analogical arguments but, perhaps surprisingly, with a priori analogical arguments. I will then argue that this does not favor a sui generis view of the analogical argument over inductivist views, and attempt to show that a confirmation-theoretic approach to analogical inference makes the best sense of our intuitions about the strength of analogical arguments.

Analogical reasoning in restructuring scientific knowledge

European Journal of Psychology of Education, 1996

This study presents the results of an experiment which investigated analogical reasoning in knowledge acquisition in a natural school setting. The aims were to evaluate the efficiency of analogy in the conceptual restructuring of a science topic and compare the effects of analogy in different learning conditions. Two analogical topics of physics (water flow and heat flow) were studied by means of two experiments performed in the classroom with concrete objects. Eighty-four 5th graders, divided into three experimental conditions (given analogy, constructed analogy, no analogy), took part in the study. The quantitative analysis mainly confirms the hypothesis that analogy can be a productive way to trigger a process of knowledge restructuring while students learn a new topic. However, the effective use of the analogy was affected by the experimental condition: When the analogy was constructed by the learners themselves, instead of being presented and justified by the teacher, it acted indeed as a more powerful tool in understanding the new topic which required changing their initial conceptions. The qualitative analysis shows the children’s explanations of the heat flow phenomenon and different conceptual outcomes of the learning process. Finally, educational implications are considered.

The Analogy Theory of Thinking*

Dialectica, 2005

The paper deals with a doctrine called the analogy theory of thinking. Its contemporary proponents have been Wilfried Sellars and Peter Geach. The paper is an attempt to give an exact formulation for one answer to the question concerning the relation of thought and speech. That answer is a reduced of Sellar's theory. A semiformal explication of the view is suggested by means of the classical analogy theory and Bochenski's treatment of that theory. It is argued that even if the analogy theory of thinking is subject to serious criticism, it offers us tools for considering some old philosophical problems in a new way.