On monotonicity of dispute trees as explanations for case-based reasoning with abstract argumentation

Recent work on explainability raises the question of what different types of explanations actually mean. One idea is that explanations can reveal information about the behaviour of the model on a subset of the input space. When this way of interpreting explanations is thought as an interactive process, inferences from explanations can be seen as a form of reasoning. In the case of case-based reasoning with abstract argumentation (AA-CBR), previous work has used arbitrated dispute trees as a methodology for explanation. Those are dispute trees where nodes are seen as losing or winning depending on the outcome for the new case under consideration. In this work we show how arbitrated dispute trees can be readapted for different inputs, which allows a broader interpretation of them, capturing more of the input-output behaviour of the model. We show this readaptation is correct by construction, and thus the resulting reasoning based on this reuse is monotonic and thus necessarily a faithful explanation

Form without formalism

The systematisation of deductive inference can yield an account of the structure of sentences (propositions, thoughts) involved in such inference. In mainstream contemporary analytic philosophy, the idea of "logical form" is linked, explicitly or implicitly, with the idea of such a systematisation. But this is not the only thing one might mean by "logical form". An enquiry into the structures of thoughts can be motivated by considerations besides inferential behaviour. In this dissertation I sketch an alternative conception according to which the uncovering of the logical structure of discourse proceeds from no single principle but rather piecemeal, from region of discourse to region of discourse. On this conception, the availability of a syntactic characterisation of the valid inference patterns in which a judgment participates is not a necessary condition for the attribution to it of a certain logical form.I argue that Frege's revolutionary application of function-argument analysis to logic plays a central rôle in his equation of the categories in terms of which to ascribe structure to thoughts with the syntactic categories needed for the systematisation of inference. Though the application is plausible in the case of mathematics, I argue that function-argument analysis is ill suited to the analysis of predicative structure generally. As an illustration of this claim, following Michael Thompson's lead, I discuss "natural-historical judgments," a type of generic judgment about living things. I walk through a series of formal-semantic proposals for generic sentences, arguing that each founders on its imposition of function-argument analysis on natural-historical judgments. The logical form of natural-historical judgments is not to be understood on the functional model; the categories deployed in their grasp are not explained by their use in codifying inference patterns.I associate the view that the uncovering of logical form is a piecemeal, unprincipled affair with the later work of Wittgenstein. I bring out how Wittgenstein's engagement in the Tractatus with Frege's and Russell's conceptions of logic paves the way for his later development of the notion of grammar in the Investigations, in order to show how the conception of form I advocate has a genuine claim to logicality

A rule-based ontological framework for the classification of molecules

BACKGROUND: A variety of key activities within life sciences research involves integrating and intelligently managing large amounts of biochemical information. Semantic technologies provide an intuitive way to organise and sift through these rapidly growing datasets via the design and maintenance of ontology-supported knowledge bases. To this end, OWL-a W3C standard declarative language- has been extensively used in the deployment of biochemical ontologies that can be conveniently organised using the classification facilities of OWL-based tools. One of the most established ontologies for the chemical domain is ChEBI, an open-access dictionary of molecular entities that supplies high quality annotation and taxonomical information for biologically relevant compounds. However, ChEBI is being manually expanded which hinders its potential to grow due to the limited availability of human resources. RESULTS: In this work, we describe a prototype that performs automatic classification of chemical compounds. The software we present implements a sound and complete reasoning procedure of a formalism that extends datalog and builds upon an off-the-shelf deductive database system. We capture a wide range of chemical classes that are not expressible with OWL-based formalisms such as cyclic molecules, saturated molecules and alkanes. Furthermore, we describe a surface 'less-logician-like' syntax that allows application experts to create ontological descriptions of complex biochemical objects without prior knowledge of logic. In terms of performance, a noticeable improvement is observed in comparison with previous approaches. Our evaluation has discovered subsumptions that are missing from the manually curated ChEBI ontology as well as discrepancies with respect to existing subclass relations. We illustrate thus the potential of an ontology language suitable for the life sciences domain that exhibits a favourable balance between expressive power and practical feasibility. CONCLUSIONS: Our proposed methodology can form the basis of an ontology-mediated application to assist biocurators in the production of complete and error-free taxonomies. Moreover, such a tool could contribute to a more rapid development of the ChEBI ontology and to the efforts of the ChEBI team to make annotated chemical datasets available to the public. From a modelling point of view, our approach could stimulate the adoption of a different and expressive reasoning paradigm based on rules for which state-of-the-art and highly optimised reasoners are available; it could thus pave the way for the representation of a broader spectrum of life sciences and biomedical knowledge.</p

Semantic Matchmaking of Web Resources with Local Closed-World Reasoning

Ontology languages like OWL allow for semantically rich annotation of resources (e.g., products advertised at on-line electronic marketplaces). The description logic (DL) formalism underlying OWL provides reasoning techniques that perform match-making on such annotations. This paper identifies peculiarities in the use of DL inferences for matchmaking that derive from OWL\u27s open-world semantics, analyzes local closed-world reasoning for its applicability to matchmaking, and investigates the suitability of two nonmonotonic extensions to DL, autoepistemic DLs and DLs with circumscription, for local closed-world reasoning in the matchmaking context. An elaborate example of an electronic marketplace for PC product catalogs from the e-commerce domain demonstrates how these formalisms can be used to realize such scenarios