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International Conference on Artificial General Intelligence

AGI 2018: Artificial General Intelligence pp 151–161Cite as

DSO Cognitive Architecture: Implementation and Validation of the Global Workspace Enhancement

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10999))

Abstract

An enhanced DSO Cognitive Architecture design was recently introduced to augment its cognitive functions by incorporating the Global Workspace Theory. A computational implementation of this new design is described in detail in this paper. The implementation is built as a distributed system with parallel pipelines of specialised processes, executing asynchronously. Competition initiated by these processes, and facilitated by the attention mechanism and global broadcast mechanism, leads to pipelines being dynamically created and allows disconnected pipelines to influence the processing of others. To validate the implementation, it was applied to a traffic control problem and experimental results showed increase in performance gain using the enhanced cognitive architecture.

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Author information

Authors and Affiliations

  1. Cognition and Fusion Lab 2, DSO National Laboratories, Singapore, Singapore

    Khin Hua Ng, Zhiyuan Du & Gee Wah Ng

Authors
  1. Khin Hua Ng
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  2. Zhiyuan Du
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  3. Gee Wah Ng
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Corresponding author

Correspondence to Khin Hua Ng .

Editor information

Editors and Affiliations

  1. Adams State University, Alamosa, Colorado, USA

    Matthew Iklé

  2. Odessa Competence Center for Artificial Intelligence (OCCAM), Odessa, Ukraine

    Arthur Franz

  3. Hokkaido University, Sapporo, Japan

    Rafal Rzepka

  4. SingularityNET; OpenCog; Hanson Robotics, Hong Kong, China

    Ben Goertzel

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Ng, K.H., Du, Z., Ng, G.W. (2018). DSO Cognitive Architecture: Implementation and Validation of the Global Workspace Enhancement. In: Iklé, M., Franz, A., Rzepka, R., Goertzel, B. (eds) Artificial General Intelligence. AGI 2018. Lecture Notes in Computer Science(), vol 10999. Springer, Cham. https://doi.org/10.1007/978-3-319-97676-1_15

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  • DOI: https://doi.org/10.1007/978-3-319-97676-1_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-97675-4

  • Online ISBN: 978-3-319-97676-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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