Thermodynamics 2.0 | 2022 Program: Sessions and Abstracts

Mon - Wed, July 18 - July 20 , 2022 , Boone, North Carolina

Session T03: Energy, Entropy and Information

14:00-15:00. Monday July 18, 2022

Chair: Sandro Sozzo

Title: Implementing Fuzzy Sets through Molecules and Determining their Entropy

Presenter:

  • Pier Luigi Gentili

(University of Perugia, Italy )

Bio-sketch

Pier Luigi Gentili received his Ph.D. in Chemistry from the University of Perugia in 2004. His research and teaching activities are focused on Complex Systems. He is author of the book titled “Untangling Complex Systems: A Grand Challenge for Science” published by CRC Press in 2018. Being aware that inanimate matter is driven by force-fields, whereas the interactions between biological systems are also information-based, Gentili is led by some questions like the following ones. “When does a chemical system become intelligent?” Is it possible to develop a “Chemical Artificial Intelligence?” For the Chemical Artificial Intelligence development, Pier Luigi Gentili relies upon the theory and tools of Natural Computing. In particular, he is tracing a new path in the field of Neuromorphic Engineering by using non-linear chemical systems and encoding information mainly through UV-visible signals. He is proposing methods to process Fuzzy logic by Molecular, Supramolecular, and Systems chemistry.

Author(s):

  • Pier Luigi Gentili

(University of Perugia, Italy )

  • Juan Perez-Mercader

(Harvard University, Massachusetts, USA)

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Abstract:T03.119

Abstract

Fuzzy logic is a good model of the human ability to compute with words [1]. It has been defined as a rigorous logic of vague and approximate reasoning. It is based on the theory of Fuzzy sets proposed by the engineer Lotfi Zadeh in 1965 [2]. Fuzzy logic is a valid model of the human capacity to make decisions using natural language because there are structural and functional analogies between the human nervous system and Fuzzy logic systems [3-5]. Fuzzy logic is widely used in the field of Artificial Intelligence [6].

In Chemical Artificial Intelligence [7], molecular, supramolecular, and systems chemistries are employed to mimic some human intelligence performances and process Fuzzy logic [4].

In this contribution, we present a strategy for implementing Fuzzy sets through molecules and an algorithm for determining their entropy [8]. This study will promote the development of Chemical Artificial Intelligence, but it could also spark new ideas about the origin of life on Earth. The appearance of life on Earth was like a “phase transition” [9]. Roughly 4.0 billion years ago, there was a transition from inanimate chemical systems, unable to encode, process, communicate and store information, to the living chemical systems, able to exploit the matter and energy to encode, process, send, and store information. The development of Chemical Artificial Intelligence could unveil how that unique “phase transition” happened.

 

Keywords: entropy, fuzzy logic, molecules, conformations, artificial intelligence, the origin of life.

 

[1] Zadeh, L.A. IEEE Comput. Intell. Mag. 2008, 3, 11–22.

[2] Zadeh, L.A. Inform. Control 1965, 8, 338–353.

[3] Gentili, P.L. J. Intell. Fuzzy Syst. 2014, 27, 2137–2151.

[4] Gentili, P.L. Molecules 2018, 23, 2074.

[5] Gentili, P.L. Molecules 2021, 26, 5987.

[6] Zadeh, L.A. AI Mag. 2001, 22, 73–84.

[7] Gentili, P.L. RSC Adv. 2013, 3, 25523–25549.

[8] Gentili, P.L., Perez-Mercader, J. Manuscript in preparation.

[9] Pérez-Mercader J. Physical Phenomena Underlying the Origin of Life. InLife in the Universe 2004 (pp. 27-51). Springer, Dordrecht.