Human-Centric Functional Modeling and the Metaverse

Year 2022, Volume: 2 Issue: 1, 23 - 28, 30.06.2022

Andy Williams

Abstract

Human-Centric Functional Modeling represents systems in terms of functional state spaces defined through analogy with the functional state space hypothesized to be occupied by human cognition. These functional state spaces are hypothesized to define a complete representation of the human meaning of the system being modeled, and therefore are hypothesized to define the first complete semantic model of any given system, or of information itself. One potential use of functional state spaces is to represent the physical world or any virtual world. This paper explores the barriers to and implications of using Human-Centric Functional Modeling to define a functional state space as a semantic model of any real or imaginary world, and explores how those barriers and implications impact upcoming applications such as the metaverse proposed by the company formerly known as Facebook, as well as others.

Keywords

Human-Centric Functional Modeling, functional state space, General Collective Intelligence, metaverse

References

• Suppe, F. (1989). The semantic conception of theories and scientific realism. University of Illinois Press.
• Lloyd, E. A. (1984). A semantic approach to the structure of population genetics. Philosophy of Science, 51(2), 242-264.
• Niiniluoto, I. (1987). Quantities, State Spaces, and Laws. In Truthlikeness (pp. 103-121). Springer, Dordrecht. Doi : 10.1007/978-94-009-3739-0_3
• Williams, A. E. (Accepted) A Revolution in Systems Thinking?, Proceedings 2021 Congress of the World Organization of Systems and Cybernetics (WOSC)
• Nykamp, D. (2019) "State space definition". Math Insights. Retrieved 17 November 2019.
• Laubenbacher, R., & Pareigis, B. (2001). Equivalence relations on finite dynamical systems. Advances in applied mathematics, 26(3), 237-251. Doi: doi:10.1006/aama.2000.0717
• Williams, A. E. (2020) A Model for Artificial General Intelligence. In: Goertzel B., Panov A., Potapov A., Yampolskiy R. (eds) Artificial General Intelligence. AGI 2020. Lecture Notes in Computer Science, vol 12177. Springer, Cham. Doi:10.1007/978-3-030-52152-3_38
• Williams, A. E. (2021). Human-Centric Functional Modeling and the Unification of Systems Thinking Approaches: A Short Communication. Journal of Systems Thinking. 5-5.
• Williams, A. E. (2022, February 1). The Importance of Representing the Physical Universe or Virtual Universes in Functional State Space to the Progress of Physics. Retrieved from osf.io/preprints/africarxiv/54qrz
• Williams, A. E. (2021) "Cognitive Computing and its Relationship to Computing Methods and Advanced Computing from a Human-Centric Functional Modeling Perspective", In: Pal R. and Shukla K. P. (eds), SCRS Conference Proceedings on Intelligent Systems, SCRS, New Delhi, India. pp. 16-33. Doi:10.52458/978-93-91842-08-6-9
• Williams, A. E. (2022, February 1). Modeling Biological Systems Using Functional State Spaces. Retrieved from osf.io/preprints/africarxiv/6k4z5
• Bandara, M., Rabhi, F. (2020).“Semantic modeling for engineering data analytics solutions.” Semantic Web 11: 525-547.
• Burgdorf, A., Pomp, A., & Meisen, T. (2020). Towards NLP-supported Semantic Data Management. arXiv preprint arXiv:2005.06916.
• Nielsen, F. Å., & Hansen, L. K. (2020). Creating semantic representations. In: Sikström S., Garcia D. (eds) Statistical Semantics. Springer, Doi:10.1007/978-3-030-37250-7_2 Cham.
• Woolley, A. W., Chabris, C. F., Pentland, A., Hashmi, N., & Malone, T. W. (2010). Evidence for a collective intelligence factor in the performance of human groups. science, 330(6004), 686-688.
• Williams, A. E. (2020, July 11). Human Intelligence and General Collective Intelligence as Phase Changes in Animal Intelligence. Doi:10.31234/osf.io/dr8qn
• Williams, A. E. (2020, April 17). Using a Functional Modeling Framework to Compare Some Leading Models of Consciousness. Doi:10.31234/osf.io/8bzv6
• Williams, A. E. (2022, March 12). Automating the Process of Generalization. Doi:10.31730/osf.io/fb4us
• Williams, A. E. (2021) Are wicked problems a lack of general collective intelligence?. AI & Soc (2021). Doi:10.1007/s00146-021-01297-8
• Williams, A. E. (2022) Is General Collective Intelligence a Reliable Path Towards Achieving Green Growth, International Journal of Global Environmental Change, in press (2022)
• Williams, A. E. (2022, February 1). Is Sustainability a Pattern of Solution in a Functional State Space?. Retrieved from osf.io/preprints/africarxiv/cb2xh
• Williams, A. E.(2022) General Collective Intelligence as a Platform for Social Technology, Proceedings of the 2nd International Conference on Pervasive Computing and Social Networking (ICPCSN 2022), in press (2022)