RO EN
Symbolic Deductive Reasoning using Connectionist Models
Authors: Mihai Horia Zaharia, Florin Leon, Dan Galea
Keywords: Artificial intelligence, cognitive agents, schemata, knowledge representation, deductive reasoning, neural networks.
– 0.40 Mb
Keywords: Artificial intelligence, cognitive agents, schemata, knowledge representation, deductive reasoning, neural networks.
Abstract
In this paper, we try to combine the possibility of symbolic deductive reasoning with the learning capability of the connectionist models. We introduce several algorithms for learning relations between concepts and finding paths in a transitive manner between learned concepts. An application that implements the proposed model is described and a number of case studies are presented.Mihai Horia Zaharia, Florin Leon, Dan Galea
Department of Automatic Control
and Computer Engineering
Technical University "Gh. Asachi"
Iasi
Department of Automatic Control
and Computer Engineering
Technical University "Gh. Asachi"
Iasi
Fulltext
– 0.40 Mb
Contents
- On quasistability of a vector combinatorial problem with Σ-MINMAX and Σ-MINMIN partial criteria
- Real Time Embedded Moving Objects Detector - Study and Implementation Within Virtex FPGA Technology
- Contrastive Meanings of the Terms "Predicative" and "Predicational" in Various Linguistic Theories (II)
- Deductive databases and P systems
- Software Development Processes
- NeoSite: A simple Content Management System
- Symbolic Deductive Reasoning using Connectionist Models
- Information about the Second Conference of the Mathematical Society of the Republic of Moldova
