Children's mental representation of referential relations : representational partitioning and "theory of mind"

In six experiments I investigated children’s handling of intensional contexts. The results were described in terms of a developmental extension of Fauconnier’s mental spaces account of meaning representation. Implications for children’s mentalistic development were explored. In chapter 1 I considered the “referential opacity” raised by the representational nature of the mind. I interpreted the findings of Russell (1987) as evidence for a developmental dissociation between handling of intensional contexts - due to the partial nature of representations - and “intentional” referential problems - due to representations being outdated or hypothetical. In experiments 1-3 I demonstrated this dissociation explicitly, and showed that it extended to non-linguistic intensional contexts. Experiments 4 &5 showed correlations between children’s handling of intensional contexts and linguistic ambiguity, which I explained by their common requirement that representational content be held as partial. Experiment 6 showed that children’s handling of intensional questions (and mentalistic explanations) improved after observing incorrect action on the basis of partial knowledge. This effect of supporting context was short-lived, suggesting that it supported on-line activity not question comprehension. After earlier success with out-dated and hypothetical representations, children’s handling of partial representations at 6-7 years explains their concurrent late success with intensional contexts and linguistic ambiguity, and constitutes a qualitative change in their representational abilities

Onset of an outline map to get a hold on the wildwood of clustering methods

The domain of cluster analysis is a meeting point for a very rich multidisciplinary encounter, with cluster-analytic methods being studied and developed in discrete mathematics, numerical analysis, statistics, data analysis and data science, and computer science (including machine learning, data mining, and knowledge discovery), to name but a few. The other side of the coin, however, is that the domain suffers from a major accessibility problem as well as from the fact that it is rife with division across many pretty isolated islands. As a way out, the present paper offers an outline map for the clustering domain as a whole, which takes the form of an overarching conceptual framework and a common language. With this framework we wish to contribute to structuring the domain, to characterizing methods that have often been developed and studied in quite different contexts, to identifying links between them, and to introducing a frame of reference for optimally setting up cluster analyses in data-analytic practice.Comment: 33 pages, 4 figure

Metaphysical Explanation and the Inference to the Best Explanation (BA thesis)

Inference to the Best Explanation, roughly put, appeals to the explanatory power of a theory or hypothesis (relative to some data set) as constituting epistemic justification for it. Inference to the Best Explanation (henceforth IBE) is a tool widely employed among all reasoners alike, from the empirical sciences to ordinary life. Philosophical discussions do not differ in the usualness of explanatory appeals of this kind during serious argument. Often enough, the appeal is dialectically blocked, as many of our epistemic peers in philosophy offer reasons to be skeptical of IBE. Our aim with this monograph is to assess one worry that have been raised about this mode of inference: That explanatory power is not truth-conducive. We begin by discussing general features of inferences and then formulating IBE in detail. Afterward, we explicate and apply a canonical understanding of what an explanation is. This will lead to a certain understanding of explanatory power. We undergo a case study to defend the thesis that this kind of explanatory power is indeed epistemically irrelevant – unless, perhaps, when combined with other theoretical virtues. Our conclusion is that the measure what explanations are best requires taking other theoretical virtues into account, such as simplicity and unification. In this case, a complete assessment of IBE requires examining if, when, and how these alleged theoretical virtues are indeed truth-conducive

Reasoning in non-probabilistic uncertainty: logic programming and neural-symbolic computing as examples

This article aims to achieve two goals: to show that probability is not the only way of dealing with uncertainty (and even more, that there are kinds of uncertainty which are for principled reasons not addressable with probabilistic means); and to provide evidence that logic-based methods can well support reasoning with uncertainty. For the latter claim, two paradigmatic examples are presented: Logic Programming with Kleene semantics for modelling reasoning from information in a discourse, to an interpretation of the state of affairs of the intended model, and a neural-symbolic implementation of Input/Output logic for dealing with uncertainty in dynamic normative context

Introduction: Possible Worlds Theory Revisited

This volume systematically outlines the theoretical underpinnings of the possible worlds approach, provides updated methods for analyzing fictional narrative, and profiles those methods via the analysis of a range of different texts, ..

Concepts, Frames and Cascades in Semantics, Cognition and Ontology

This open access book presents novel theoretical, empirical and experimental work exploring the nature of mental representations that support natural language production and understanding, and other manifestations of cognition. One fundamental question raised in the text is whether requisite knowledge structures can be adequately modeled by means of a uniform representational format, and if so, what exactly is its nature. Frames are a key topic covered which have had a strong impact on the exploration of knowledge representations in artificial intelligence, psychology and linguistics; cascades are a novel development in frame theory. Other key subject areas explored are: concepts and categorization, the experimental investigation of mental representation, as well as cognitive analysis in semantics. This book is of interest to students, researchers, and professionals working on cognition in the fields of linguistics, philosophy, and psychology

On Inter-Theoretic Relations and Scientific Realism

This thesis addresses three contemporary debates in the philosophy of science: namely, scientific realism, emergence, and theoretical equivalence. The thesis brings logico-semantic tools of the analytic tradition—about syntactic and semantic construals of theories, and about extensions and intensions—to bear on these debates. The thesis has two parts: Part I (Chapters 1-3) lays out the overall framework about scientific theories, scientific realism, and emergence. Part II (Chapters 4-6) develops more detailed themes. Part I first gives a conception of a scientific theory (Chapter 1), using logico-semantic tools that will be used in the rest of the thesis. Chapter 2 then brings these tools to bear on the debate about scientific realism, by construing the continuity of theories as a matter of extensions. The resulting position is a modest scientific realism, according to which one is justified in believing what confirmed theories say about extensions but not, in general, about intensions. I dub it ‘extensional scientific realism’. Chapter 3 proposes an account of the distinction between ontological and epistemic emergence, based on an explication of the notion of ‘novel reference’. The ontological emergence of one theory from another is defined as the failure of an appropriate linkage map between the two theories to ‘‘mesh’’ with the two theories’ interpretations. In Part II, Chapter 4 first develops a notion of theoretical equivalence, and introduces duality in physics, as an appropriate isomorphism between theories. The Chapter discusses the relation between duality and theoretical equivalence in philosophy of science. Chapter 5 discusses the heuristic roles of dualities in theory construction. It develops a distinction between the theoretical and heuristic functions of scientific theories, and illustrates the heuristic function of duality in theory construction. Chapter 6 discusses how theories without a spacetime can lead to scientific understanding. To this end, the Chapter describes three theoretical tools that are often used in theory construction and which lead to understanding, both in cases with and cases without straightforward spacetime visualisation.Trinity College, Cambridge Black Hole Initiative, Harvard Universit

On Inter-Theoretic Relations and Scientific Realism

This thesis addresses three contemporary debates in the philosophy of science: namely, scientific realism, emergence, and theoretical equivalence. The thesis brings logico-semantic tools of the analytic tradition--about syntactic and semantic construals of theories, and about extensions and intensions--to bear on these debates. The thesis has two parts: Part I (Chapters 1-3) lays out the overall framework about scientific theories, scientific realism, and emergence. Part II (Chapters 4-6) develops more detailed themes. Part I first gives a conception of a scientific theory (Chapter 1), using logico-semantic tools that will be used in the rest of the thesis. Chapter 2 then brings these tools to bear on the debate about scientific realism, by construing the continuity of theories as a matter of extensions. The resulting position is a modest scientific realism, according to which one is justified in believing what confirmed theories say about extensions but not, in general, about intensions. I dub it 'extensional scientific realism'. Chapter 3 proposes an account of the distinction between ontological and epistemic emergence, based on an explication of the notion of 'novel reference'. The ontological emergence of one theory from another is defined as the failure of an appropriate linkage map between the two theories to "mesh" with the two theories' interpretations. In Part II, Chapter 4 first develops a notion of theoretical equivalence, and introduces duality in physics, as an appropriate isomorphism between theories. The Chapter discusses the relation between duality and theoretical equivalence in philosophy of science. Chapter 5 discusses the heuristic roles of dualities in theory construction. It develops a distinction between the theoretical and heuristic functions of scientific theories, and illustrates the heuristic function of duality in theory construction. Chapter 6 discusses how theories without a spacetime can lead to scientific understanding. To this end, the Chapter describes three theoretical tools that are often used in theory construction and which lead to understanding, both in cases with and cases without straightforward spacetime visualisation

Reasoning over Taxonomic Change: Exploring Alignments for the Perelleschus Use Case

abstract: Classifications and phylogenetic inferences of organismal groups change in light of new insights. Over time these changes can result in an imperfect tracking of taxonomic perspectives through the re-/use of Code-compliant or informal names. To mitigate these limitations, we introduce a novel approach for aligning taxonomies through the interaction of human experts and logic reasoners. We explore the performance of this approach with the Perelleschus use case of Franz & Cardona-Duque (2013). The use case includes six taxonomies published from 1936 to 2013, 54 taxonomic concepts (i.e., circumscriptions of names individuated according to their respective source publications), and 75 expert-asserted Region Connection Calculus articulations (e.g., congruence, proper inclusion, overlap, or exclusion). An Open Source reasoning toolkit is used to analyze 13 paired Perelleschus taxonomy alignments under heterogeneous constraints and interpretations. The reasoning workflow optimizes the logical consistency and expressiveness of the input and infers the set of maximally informative relations among the entailed taxonomic concepts. The latter are then used to produce merge visualizations that represent all congruent and non-congruent taxonomic elements among the aligned input trees. In this small use case with 6-53 input concepts per alignment, the information gained through the reasoning process is on average one order of magnitude greater than in the input. The approach offers scalable solutions for tracking provenance among succeeding taxonomic perspectives that may have differential biases in naming conventions, phylogenetic resolution, ingroup and outgroup sampling, or ostensive (member-referencing) versus intensional (property-referencing) concepts and articulations.The article is published at http://journals.plos.org/plosone/article?id=10.1371/journal.pone.011824