Much of cognitive research on deductive reasoning has been preoccupied with advocating for or against visuospatial (mental model theory) or linguistic/syntactic (mental logic theory) models of logical reasoning. Neuroimaging studies bear on this issue by pointing to both language-based and visuospatial systems being engaged during logical reasoning, and by raising additional issues not anticipa...

Current theories of human deductive reasoning make different claims about the representation of logical statements in memory. Syntactically-based theories claim that abstract logical forms are represented veridically in memory, separate from content, whereas semantic theories propose that naïve reasoners represent combinations of possibilities that are based on the content of statements. We tes...

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...

One of the most important tasks in database technology is to combine the following activities: data mining or inferring knowledge from data and query processing or reasoning on acquired knowledge. The solution of this task requires a logical language with unified syntax and semantics for integrating deductive (using knowledge) and inductive (acquiring knowledge) reasoning. In this paper, we pro...

While inductive and deductive reasoning are considered distinct logical and psychological processes, little is known about their respective neural basis. To address this issue we scanned 16 subjects with fMRI, using an event-related design, while they engaged in inductive and deductive reasoning tasks. Both types of reasoning were characterized by activation of left lateral prefrontal and bilat...

Three common approaches for deriving or predicting instantiated relations are information extraction, deductive reasoning and machine learning. Information extraction uses subsymbolic unstructured sensory information, e.g. in form of texts or images, and extracts statements using various methods ranging from simple classifiers to the most sophisticated NLP approaches. Deductive reasoning is bas...

Logic is useful for reasoning and knowledge representation in AI systems. Logical reasoning has an advantage over other forms of reasoning in that it has strong theoretical foundations. But logical reasoning also has a disadvantage: it is computationally difficult. In addition, when logical reasoning is used in physical autonomous agents there might exist real-time requirements. Performing comp...

We present a conceptual description of nonmonotonic formalisms as essentially two-layered reasoning systems consisting of a monotonic logical system, coupled with a mechanism of a reasoned choice of default assumptions. On this ‘surgery’, the main features of a nonmonotonic formalism are determined by the interplay between its logical basis and the nonmonotonic overhead. Furthermore, it allows ...