We are developing a laboratory notebook system known as the Genetics Deductive Database. Currently our prototype provides storage for biological facts and rules with flexible access via an interactive graphical display. We have introduced a formal basis for the representation and reasoning necessary to order genome map data and handle the uncertainty inherent in biological data. We aim to suppo...

This paper studies a computational logic for dishonest reasoning. We introduce logic programs with disinformation to represent and reason with dishonesty. We then consider two different cases of dishonesty: deductive dishonesty and abductive dishonesty. The former misleads another agent to deduce wrong conclusions, while the latter interrupts another agent to abduce correct explanations. In ded...

Stock trend forecasting is a one of the main factors in choosing the best investment, hence prediction and comparison of different firms’ stock trend is one method for improving investment process. Stockholders need information for forecasting firm’s stock trend in order to make decision about firms’ stock trading. In this study stock trend, forecasting performs by data mining algorithm. It sho...

Distributional semantics focuses on the automatic construction of a semantic model based on the statistical distribution of colocated words in large-scale texts. Deductive reasoning is a fundamental component for semantic understanding. Despite the generality and expressivity of logical models, from an applied perspective, deductive reasoners are dependent on highly consistent conceptual models...

The purpose of this study is to examine how pre-service elementary teachers generalize a non-linear figural pattern task and justify their generalizations. More specifically, focuses on strategies reasoning types employed by throughout generalization justification processes. Data were collected from 32 who enrolled in the Elementary Teacher Education program university, Turkey. During data coll...

This work is the second part of a general similarity-based theory of case-based reasoning (CBR), which moves CBR towards a firm theoretical foundation based on similarity-based reasoning. This paper will first examine abductive CBR and deductive CBR and propose a knowledge-based model for integrating abductive CBR and deductive CBR. It then proposes similarity-based models for rule-based and fu...

A method of deductive learning is developed to control deductive inference Our goal is to im prove problem solving time by experience when that experience monotonically adds knowledge to the knowledge base In particular for deductive reasoning systems where partial results are saved dur ing a derivation and at least some partial results are themselves deduction rules we suggest ways of taking m...

DisLog is a system for reasoning in disjunctive deductive databases. It seeks to combine features of disjunctive logic programming, such as the support for incomplete information, with those of deductive databases, such as all{result inference capabilities. Several basic operators are provided for logical and non{monotonic reasoning: The logical consequence operator derives all logically implie...

We address the semantics and normative questions for reasoning with presumptive arguments: How are presumptive arguments grounded in interpretations; and when are they evaluated as correct? For deductive and uncertain reasoning, classical logic and probability theory provide canonical answers to these questions. Staying formally close to these, we propose case models and their preferences as fo...