Publication:
Establishing a roadmap and metrics for conscious machines development

Loading...
Thumbnail Image

Advisors

Tutors

Editor

Publication date

Defense date

Journal Title

Journal ISSN

Volume Title

Publisher

IEEE

Serie/Núm

Impact
Google Scholar
Export

Research Projects

Research Projects

Organizational Units

Journal Issue

To cite this item, use the following identifier: https://hdl.handle.net/10016/10430

Abstract

From the point of view of Cognitive Informatics, consciousness can be considered as a grand integration of a number of cognitive processes. Intuitive definitions of consciousness generally involve perception, emotions, attention, self-recognition, theory of mind, volition, etc. Due to this compositional definition of the term consciousness it is usually difficult to define both what is exactly a conscious being and how consciousness could be implemented in artificial machines. When we look into the most evolved biological examples of conscious beings, like great apes or humans, the vast complexity of observed cognitive interactions in conjunction with the lack of comprehensive understanding of low level neural mechanisms makes the reverse engineering task virtually unreachable. With the aim to effectively address the problem of modeling consciousness at a cognitive level, in this work we propose a concrete developmental path in which key stages in the progressive process of building conscious machines are identified and characterized. Furthermore, a method for calculating a quantitative measure of artificial consciousness is presented. The application of the proposed framework is illustrated with the comparative study of different software agents designed to compete in a first-person shooter video game.

Note

Proceeding of: 8th IEEE International Confenrence on Cognitive Informatics (ICCI'09). Kowloon, Hong Kong, 15-17 June, 2009

ODS

Funder

Research project

Bibliographic citation

Proceedings of the 8th IEEE International Conference on Cognitive Informatics (ICCI'O9), pp.94-101.

Table of contents

Has version

Is version of

Related dataset

Related Publication

Is part of