Proceedings Third Annual Symposium on Human Interaction with Complex Systems. HICS'96

1996 ◽  
Keyword(s):  
Complex Systems ◽  
Human Interaction ◽  
Annual Symposium

scholarly journals Quantum Probabilistic Models Using Feynman Diagram Rules for Better Understanding the Information Diffusion Dynamics in Online Social Networks

2020 ◽  
Vol 34 (10) ◽  
pp. 13730-13731
Author(s):  
Ece C. Mutlu
Keyword(s):  
Social Networks ◽  
Social Learning ◽  
Complex Systems ◽  
Bayesian Networks ◽  
Online Social Networks ◽  
Information Diffusion ◽  
Probabilistic Models ◽  
Human Interaction ◽  
Multi Agent Systems ◽  
Diffusion Dynamics

This doctoral consortium presents an overview of my anticipated PhD dissertation which focuses on employing quantum Bayesian networks for social learning. The project, mainly, aims to expand the use of current quantum probabilistic models in human decision-making from two agents to multi-agent systems. First, I cultivate the classical Bayesian networks which are used to understand information diffusion through human interaction on online social networks (OSNs) by taking into account the relevance of multitude of social, psychological, behavioral and cognitive factors influencing the process of information transmission. Since quantum like models require quantum probability amplitudes, the complexity will be exponentially increased with increasing uncertainty in the complex system. Therefore, the research will be followed by a study on optimization of heuristics. Here, I suggest to use an belief entropy based heuristic approach. This research is an interdisciplinary research which is related with the branches of complex systems, quantum physics, network science, information theory, cognitive science and mathematics. Therefore, findings can contribute significantly to the areas related mainly with social learning behavior of people, and also to the aforementioned branches of complex systems. In addition, understanding the interactions in complex systems might be more viable via the findings of this research since probabilistic approaches are not only used for predictive purposes but also for explanatory aims.

scholarly journals PSYCHOLOGICAL ASPECTS OF THE PROBLEM OF ARTIFICIAL INTELLIGENCE

2020 ◽  
pp. 33-53
Author(s):  
С.Ф. Сергеев
Keyword(s):  
Artificial Intelligence ◽  
Complex Systems ◽  
Psychological Research ◽  
Psychological Aspects ◽  
Human Interaction ◽  
General Psychology ◽  
Conceptual Apparatus ◽  
History Of ◽  
Engineering Psychology ◽  
Artificial Intelligence Systems

В статье дан краткий анализ истории появления и развития проблематики искусственного интеллекта и связанных с нею актуальных направлений в области общей психологии, инженерной психологии и эргономики. При создании систем и технологий искусственного интеллекта, порождаемых эволюцией техногенной среды человеческой цивилизации необходимо учитывать вопросы обеспечения взаимодействия человека с организованной эволюционирующей средой. Рассматриваются перспективные направления психологических исследований и возможные проблемы при использовании в этих областях концептуально-понятийного аппарата постнеклассический психологии, философии самоорганизующихся сложных систем. The article provides a brief analysis of the history of the emergence and development of artificial intelligence issues and related topical areas in the field of General psychology, engineering psychology and ergonomics. When creating artificial intelligence systems and technologies generated by the evolution of the technogenic environment of human civilization, it is necessary to take into account the issues of ensuring human interaction with the organized evolving environment. The article considers promising areas of psychological research and possible problems when using the conceptual and conceptual apparatus of post-non-classical psychology and the philosophy of self-organizing complex systems in these areas.

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