Generative Logic with Time: Beyond Logical Consistency and Statistical Possibility

This paper gives a theory of inference to logically reason symbolic knowledge fully from data over time. We propose a temporal probabilistic model that generates symbolic knowledge from data. The statistical correctness of the model is justified in terms of consistency with Kolmogorov's axioms, Fenstad's theorems and maximum likelihood estimation. The logical correctness of the model is justified in terms of logical consequence relations on propositional logic and its extension. We show that the theory is applicable to localisation problems.Comment: arXiv admin note: text overlap with arXiv:2206.1317

Bayesian model selection in statistical construction of justification

Argumentation mining involves identification of an attack relation between natural language sentences. Bayesian inference characterizing argument-based reasoning addresses this issue by calculating the posterior distribution over attack relations given acceptability statuses of arguments. This paper discusses the use of Bayesian model selection where graph-theoretic properties impose restrictions on the graphic structure of attack relations

Bayesian model selection in statistical construction of justification

Argumentation mining involves identification of an attack relation between natural language sentences. Bayesian inference characterizing argument-based reasoning addresses this issue by calculating the posterior distribution over attack relations given acceptability statuses of arguments. This paper discusses the use of Bayesian model selection where graph-theoretic properties impose restrictions on the graphic structure of attack relations

Paretian argumentation frameworks for Pareto optimal arguments

Argument-based reasoning offers promising interaction and computation mechanisms for multi-agent negotiation and deliberation. Arguments in this context are typically statements of beliefs or actions related to agents' subjective values, preferences and so on. Consequences of such arguments can and should be evaluated using various criteria, and therefore it is desirable that semantics supports these criteria as principles for accepting arguments. This article gives an instance of Dung's abstract argumentation framework to deal with Pareto optimality, i.e. a fundamental criterion for social welfare. We show that the instance allows Dung's acceptability semantics to interpret Pareto optimal arguments, without loss of generality. We discuss the prospects of justified Pareto optimal arguments and Pareto optimal extensions

A mild and convenient synthesis of N-carbobenzyloxy ketimines

金沢大学医薬保健研究域薬学系N-Carbobenzyloxy (Cbz) ketimines were prepared conveniently from N-Cbz amines by oxidation with N-tert-butylbenzenesulfinimidoyl chloride. © The Royal Society of Chemistry 2006

Formalising an aspect of argument strength: degrees of attackability

This paper formally studies a notion of dialectical argument strength in terms of the number of ways in which an argument can be successfully attacked in expansions of an abstract argumentation framework. The proposed model is abstract but its design is motivated by the wish to avoid overly limiting assumptions that may not hold in particular dialogue contexts or in particular structured accounts of argumentation. It is shown that most principles for gradual argument acceptability proposed in the literature fail to hold for the proposed notion of dialectical strength, which clarifies their rational foundations and highlights the importance of distinguishing between logical, dialectical and rhetorical argument strength