Developmental and Evolutionary Lexicon Acquisition in Cognitive AgentsRobots with Grounding Principle: A Short Review

Joint Authors

Rasheed, Nadia
Amin, Shamsudin H. M.

Source

Computational Intelligence and Neuroscience

Issue

Vol. 2016, Issue 2016 (31 Dec. 2015), pp.1-8, 8 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2016-03-16

Country of Publication

Egypt

No. of Pages

8

Main Subjects

Biology

Abstract EN

Grounded language acquisition is an important issue, particularly to facilitate human-robot interactions in an intelligent and effective way.

The evolutionary and developmental language acquisition are two innovative and important methodologies for the grounding of language in cognitive agents or robots, the aim of which is to address current limitations in robot design.

This paper concentrates on these two main modelling methods with the grounding principle for the acquisition of linguistic ability in cognitive agents or robots.

This review not only presents a survey of the methodologies and relevant computational cognitive agents or robotic models, but also highlights the advantages and progress of these approaches for the language grounding issue.

American Psychological Association (APA)

Rasheed, Nadia& Amin, Shamsudin H. M.. 2016. Developmental and Evolutionary Lexicon Acquisition in Cognitive AgentsRobots with Grounding Principle: A Short Review. Computational Intelligence and Neuroscience،Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1099806

Modern Language Association (MLA)

Rasheed, Nadia& Amin, Shamsudin H. M.. Developmental and Evolutionary Lexicon Acquisition in Cognitive AgentsRobots with Grounding Principle: A Short Review. Computational Intelligence and Neuroscience Vol. 2016, no. 2016 (2015), pp.1-8.
https://search.emarefa.net/detail/BIM-1099806

American Medical Association (AMA)

Rasheed, Nadia& Amin, Shamsudin H. M.. Developmental and Evolutionary Lexicon Acquisition in Cognitive AgentsRobots with Grounding Principle: A Short Review. Computational Intelligence and Neuroscience. 2016. Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1099806

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1099806