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A New Matrix Model for Human-AI Integration

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Proceedings of the Future Technologies Conference (FTC) 2021, Volume 1 (FTC 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 358))

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Abstract

This paper has the goal to describe the introduction of an AGI (Artificial General Intelligence) in a human organization. An organization may be composed of project leaders (vertical communication), human and non-human operations, an AGI machine that manages horizontal communication and big data. This leads to the paradigm of the Organizational Great Machine (GM) in which humans benefit from upgrade or empowerment provided by an all-encompassing artificial intelligence. An AGI has a substrate that uses Multi Agent System (MAS) where the model of an agent is defined as a belief, desire, intention (BDI) model of an agent augmented with Situations and Action (SBDIA). This provides a way of explaining future-directed intention. SBDIA has a natural model consistent with human psychology. Once artificial intelligence is introduced into the organization, we have to design new Human-Machine Integration (HMI) tools to have a successful relationship with human resources. At the end the organizational model of the MAS, called Great machine (GM), is used to provide information and transparency about the behavior of an AGI. A GM's internal model is considered as a knowledge market where knowledge flows among agents. Leontief's economic model emulates this market by providing information on how knowledge flows and how it is used. This permits more transparency and an understanding of internal processes.

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References

  1. Systems Engineering Guide for Systems of Systems, Version 1.0 (2008)

    Google Scholar 

  2. Bratman, M.E.: Intention, Plans, and Practical Reason. CSLI Publications. ISBN 1-57586-192-5 (2006)

    Google Scholar 

  3. Bratman, M.E.: Faces of Intention. Cambridge University Press. ISBN 0521631319. 978-0–521-63131-0

    Google Scholar 

  4. Rago, F.: Sentient Theory , Sentient basic agent Design_PL_REFKB_V0.2, under review

    Google Scholar 

  5. Thielscher, M.: Introduction to the fluent calculus. Electron. Trans. Artif. Intell. (1998)

    Google Scholar 

  6. Thielscher, M.: Reasoning robots - the art and science of programming robotic agents. In: Volume 33 of Applied Logic Series. Springer, Dordrecht (2005). https://doi.org/10.1007/1-4020-3069-X

  7. Leontief, W.W.: Input-Output Economics. Oxford University Press, New York (1966)

    Google Scholar 

  8. Dietzenbacher, E., Lahr, M.L. (eds.): Wassily Leontief and Input-Output Economics. Cambridge University Press (2004). https://doi.org/10.1017/CBO9780511493522

    Book  Google Scholar 

  9. Yamaguchi, H.: A cooperative hunting behavior by mobile-robot troops. The International Journal of Robotics Research 18(8), 931–940 (1999)

    Article  Google Scholar 

  10. Gazi, V., Passino, K.M.: Stability analysis of swarms. IEEE Trans. Autom. Control 48(4), 692–697 (2003)

    Article  MathSciNet  Google Scholar 

  11. Jorgenson, D.W.: Growth: Econometric General Equilibrium Modeling. The MIT Press (1998)

    Book  Google Scholar 

  12. Rao, A.S., Georgeff, M.P.: Modeling rational agents within a BDI-architecture. In: Proceedings of the 2nd International Conference on Principles of Knowledge Representation and Reasoning, pp. 473–484 (1991)

    Google Scholar 

  13. Rao, A.S. Georgeff, M.P.: BDI-agents: from theory to practice. In: Proceedings of the First International Conference on Multi-agent Systems (ICMAS 1995), San Francisco (1995)

    Google Scholar 

  14. Bratman, M.E.: Intention, Plans, and Practical Reason. CSLI Publications (1987)

    Google Scholar 

  15. Li, S.E., et al.: Dynamical modeling and distributed control of connected and automated vehicles: challenges and opportunities. IEEE Intell. Transp. Syst. Mag. 9(3), 46–58 (2017)

    Article  Google Scholar 

  16. Bouzid, M., Ligeza, A.: Temporal causal networks for simulation and diagnosis, publisher. In: Proceedings of ICECCS 1996: 2nd IEEE International Conference on Engineering of Complex Computer Systems (1996)

    Google Scholar 

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Correspondence to Francesco Rago .

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Rago, F. (2022). A New Matrix Model for Human-AI Integration. In: Arai, K. (eds) Proceedings of the Future Technologies Conference (FTC) 2021, Volume 1. FTC 2021. Lecture Notes in Networks and Systems, vol 358. Springer, Cham. https://doi.org/10.1007/978-3-030-89906-6_9

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