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  1. Cheaper Spaces.Matthieu Moullec & Igor Douven - 2025 - Minds and Machines 35 (1):1-21.
    Similarity spaces are standardly constructed by collecting pairwise similarity judgments and subjecting those to a dimension-reduction technique such as multidimensional scaling or principal component analysis. While this approach can be effective, it has some known downsides, most notably, it tends to be costly and has limited generalizability. Recently, a number of authors have attempted to mitigate these issues through machine learning techniques. For instance, neural networks have been trained on human similarity judgments to infer the spatial representation of unseen stimuli. (...)
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  • Williamson’s Abductive Case for the Material Conditional Account.Robert van Rooij, Karolina Krzyżanowska & Igor Douven - 2023 - Studia Logica 111 (4):653-685.
    InSuppose and Tell, Williamson makes a new and original attempt to defend the material conditional account of indicative conditionals. His overarching argument is that this account offers the best explanation of the data concerning how people evaluate and use such conditionals. We argue that Williamson overlooks several important alternative explanations, some of which appear to explain the relevant data at least as well as, or even better than, the material conditional account does. Along the way, we also show that Williamson (...)
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  • Towards a theory of abduction based on conditionals.Rolf Pfister - 2022 - Synthese 200 (3):1-30.
    Abduction is considered the most powerful, but also the most controversially discussed type of inference. Based on an analysis of Peirce’s retroduction, Lipton’s Inference to the Best Explanation and other theories, a new theory of abduction is proposed. It considers abduction not as intrinsically explanatory but as intrinsically conditional: for a given fact, abduction allows one to infer a fact that implies it. There are three types of abduction: Selective abduction selects an already known conditional whose consequent is the given (...)
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  • Engineering Disputed Concepts and the Meeting of Minds.Davide Coraci & Piero Avitabile - forthcoming - Topoi:1-13.
    Critical discussions can often require conceptual engineering, a process in which speakers are engaged in revising each other’s concepts. We show that the analysis of conceptual engineering can benefit from integrating argumentation theory with models of conceptual representation. Argumentation theory accounts for the argumentative moves of the discussants, allowing the detection of speakers’ conceptual disagreements, for which some fallacies can be seen as cues. Models of conceptual representation, such as Conceptual spaces and the theory of meeting of minds, allow us (...)
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  • The Role of Naturalness in Concept Learning: A Computational Study.Igor Douven - 2023 - Minds and Machines 33 (4):695-714.
    This paper studies the learnability of natural concepts in the context of the conceptual spaces framework. Previous work proposed that natural concepts are represented by the cells of optimally partitioned similarity spaces, where optimality was defined in terms of a number of constraints. Among these is the constraint that optimally partitioned similarity spaces result in easily learnable concepts. While there is evidence that systems of concepts generally regarded as natural satisfy a number of the proposed optimality constraints, the connection between (...)
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