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 “what metaphors are”. 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.
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D’Hanis, I. (2002). A Logical Approach to the Analysis of Metaphors. In: Magnani, L., Nersessian, N.J., Pizzi, C. (eds) Logical and Computational Aspects of Model-Based Reasoning. Applied Logic Series, vol 25. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0550-0_2
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DOI: https://doi.org/10.1007/978-94-010-0550-0_2
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