Journal of
Systemics, Cybernetics and Informatics
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ISSN: 1690-4524 (Online)


Peer Reviewed Journal via three different mandatory reviewing processes, since 2006, and, from September 2020, a fourth mandatory peer-editing has been added.

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Published by
The International Institute of Informatics and Cybernetics


Re-Published in
Academia.edu
(A Community of about 40.000.000 Academics)


Honorary Editorial Advisory Board's Chair
William Lesso (1931-2015)

Editor-in-Chief
Nagib C. Callaos


Sponsored by
The International Institute of
Informatics and Systemics

www.iiis.org
 

Editorial Advisory Board

Quality Assurance

Editors

Journal's Reviewers
Call for Special Articles
 

Description and Aims

Submission of Articles

Areas and Subareas

Information to Contributors

Editorial Peer Review Methodology

Integrating Reviewing Processes


Transdisciplinary Communication as a Meta-Framework of Digital Education
Rusudan Makhachashvili, Ivan Semenist
(pages: 1-6)

Multidisciplinary Learning Using Online Networking in Biomedical Engineering
Shigehiro Hashimoto
(pages: 7-12)

Augmented Intelligence for Advancing Healthcare
Mohammad Ilyas
(pages: 13-19)

A Transdisciplinary Approach to Refereeal
Russell Jay Hendel
(pages: 20-25)

The Impact of Convictions on Interlocking Systems
Teresa Henkle Langness
(pages: 26-33)

Collaborative Convergence: Finding the Language for Trans-Disciplinary Communication to Occur
Cristo Leon, James Lipuma
(pages: 34-37)

Bridging the Gap Between the World of Education and the World of Business via Standards to Develop Competences of the Future at Universities
Paweł Poszytek
(pages: 38-42)

Multidisciplinary Learning for Multifaceted Thinking in Globalized Society
Shigehiro Hashimoto
(pages: 43-48)

From Spirituality to Technontology in Education
Florent Pasquier
(pages: 49-52)

Differentiated Learning and Digital Game Based Learning: The KIDEDU Project
Eleni Tsami
(pages: 53-57)

Emerging Role of Artificial Intelligence
Mohammad Ilyas
(pages: 58-65)

Practicing Transdisciplinarity and Trans-Domain Approaches in Education: Theory of and Communication in Values and Knowledge Education (VaKE)
Jean-Luc Patry
(pages: 66-71)

Reflexive Practice for Inter and Trans Disciplinary Research in the Third Millennium
Maria Grazia Albanesi
(pages: 72-76)


 

Abstracts

 


ABSTRACT


Mathematical Physics Framework SustainingNatural Anticipation and Selection of Attention

Alfons Salden


An ambient intelligent environment is definitely a prerequisite for anticipating the needs and catching the attention of systems. But how to endow such an environment with natural anticipatory and attentive features is still a hardly ever properly addressed question. Before providing a roadmap towards such an ambient intelligent environment we first give cognitive-ergonomic accounts for how natural anticipation and selection of attention (NASA) emerge in living organisms. In particular, we describe why, when and how exploratory and goal-directed acts by living organisms are controlled while optimizing their changing and limited structural and functional capabilities of multimodal sensor, cognitive and actuator systems. Next, we describe how NASA can be embedded and embodied in sustainable intelligent multimodal systems (SIMS). Such systems allow an ambient intelligent environment to (self-) interact taking its contexts into account. In addition, collective intelligent agents (CIA) distribute, store, extend, maintain, optimize, diversify and sustain the NASA embedded and embodied in the ambient intelligent environment. Finally, we present the basic ingredients of a mathematical-physical framework for empirically modeling and sustaining NASA within SIMS by CIA in an ambient intelligent environment. An environment which is modeled this way, robustly and reliably over time aligns multi-sensor detection and fusion; multimodal fusion, dialogue planning and fission; multi actuator fission, rendering and presentation schemes. NASA residing in such an environment are then active within every phase of perception-decision-action cycles, and are gauged and renormalized to its physics. After determining and assessing across several evolutionary dynamic scales appropriate fitness, utility and measures, NASA can be realized by reinforcement learning and self-organization.

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