IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Propositional Logic Syntax Acquisition Using Induction and Self-Organisation

Propositional Logic Syntax Acquisition Using Induction and Self-Organisation
View Sample PDF
Author(s): Josefina Sierra (Universidad Politécnica de Cataluña, Spain)and Josefina Santibáñez (Universidad de La Rioja, Spain)
Copyright: 2009
Pages: 14
Source title: Handbook of Research on Agent-Based Societies: Social and Cultural Interactions
Source Author(s)/Editor(s): Goran Trajkovski (Laureate Education Inc., USA)and Samuel G. Collins (Towson University, USA)
DOI: 10.4018/978-1-60566-236-7.ch013

Purchase

View Propositional Logic Syntax Acquisition Using Induction and Self-Organisation on the publisher's website for pricing and purchasing information.

Abstract

This chapter addresses the problem of the acquisition of the syntax of propositional logic. An approach based on general purpose cognitive capacities such as invention, adoption, parsing, generation, and induction is proposed. Self-organisation principles are used to show how a shared set of preferred lexical entries and grammatical constructions, that is, a language, can emerge in a population of autonomous agents which do not have any initial linguistic knowledge. Experiments in which a population of autonomous agents constructs a grammar that allows communicating the formulas of a propositional logic language are presented. These experiments extend previous work by considering a larger population and a much larger search space of grammar rules. In particular, the agents are allowed to order the expressions associated with the constituents of a logical formula in arbitrary order. Previous work assumed that the expressions associated with the connectives should be placed in the first position of the sentence.

Related Content

Rafael Martí, Juan-José Pantrigo, Abraham Duarte, Vicente Campos, Fred Glover. © 2013. 21 pages.
Peng-Yeng Yin, Fred Glover, Manuel Laguna, Jia-Xian Zhu. © 2013. 20 pages.
Volodymyr P. Shylo, Oleg V. Shylo. © 2013. 10 pages.
Tabitha James, Cesar Rego. © 2013. 19 pages.
Gary G. Yen, Wen-Fung Leong. © 2013. 25 pages.
Shi Cheng, Yuhui Shi, Quande Qin. © 2013. 29 pages.
Xin-She Yang. © 2013. 12 pages.
Body Bottom