The Natural Language for Artificial Intelligence (Cognitive Data Science in Sustainable Computing) - Softcover

Über die Autorinnen und Autoren

Dionéia Motta Monte-Serrat is a Post-doctoral Researcher at the Department of Computation and Mathematics of Faculty of Philosophy, Sciences and Letters of Ribeirao Preto – University of Sao Paulo, FFCLRP-USP, Brazil; Collaborating researcher at Language Institute of University of Campinas, IEL-UNICAMP, Brazil. Faculty Member at University of Ribeirao Preto, UNAERP, Brazil. Direct Doctoral degree in Psychology, FFCLRP-USP, Brazil. Doctoral degree program partly completed at Université Paris III, Sorbonne Nouvelle (2010, CAPES-BEX). Internship at École des Hautes Études en Sciences Sociales, Paris (2012, FAPESP). Undergraduate degrees in Languages and Law. Member of the British Wittgenstein Society. Associate Researcher, National Science Network for Education (Rede CpE, Brazil). Research interest: Neuroscience; Neurolinguistics; Neurocognition; Brain Impairment; Artificial Intelligence; Neurophysiology; Natural Language, Education, Social inclusion.

Dr. Carlo Cattani is Full Professor of Mathematical Physics and Applied Mathematics at the Department of Economics, Engineering, Society and Enterprise (DEIM) at Università degli Studi della Tuscia, Viterbo, Italy. He has been previously appointed as Professor and Research Fellow at the Department of Mathematics, University of Rome La Sapienza, and Department of Mathematics, University of Salerno. Dr. Cattani has been a Research Fellow at the Italian Council of Research (CNR) and Visiting Research Fellow at the Physics Institute of Stockholm University. His main scientific research interests are focused on numerical and computational methods, mathematical models and methods, time series and data analysis, computer methods and simulations. Dr. Cattani is co-author of several books, including The Natural Language for Artificial Intelligence, Elsevier Academic Press; Wavelet and Wave Analysis as Applied to Materials with Micro or Nanostructure, World Scientific Publishing; Fractional Dynamics, De Gruyter; Computational Methods for Data Analysis, De Gruyter; Fractal Analysis: Basic Concepts and Applications, World Scientific Publishing; Symmetry and Complexity, Mdpi AG; and Advances in Mathematical Modelling: Applied Analysis and Computation, Springer. He has made significant contributions to scientific and mathematical research on fundamental topics such as numerical methods, dynamical systems, fractional calculus, fractals, wavelets, nonlinear waves, and data analysis. Dr. Cattani is Editor in Chief of the journals Fractal and Fractional and Information Sciences Letters.

Von der hinteren Coverseite

The Natural Language for Artificial Intelligence presents natural language as the next frontier because it identifies something that is most sought after by scholars: The universal structure of language that gives rise to the respective universal algorithm. In short, this book presents the biological and logical structure typical of human language in its dynamic mediating process between reality and the human mind that, at the same time, interprets the context of reality. It is a non-static approach to natural language, which is defined as a complex system whose parts interact with the ability to generate a new quality of behavior and whose dynamic elements are mapped in order to be understood and executed by intelligent systems, guiding the paradigms of cognitive computing.

The book explains linguistic functioning in the dynamic process of human cognition when forming meaning. After that, an approach to artificial intelligence (AI) is outlined, which works with a more restricted concept of natural language, leading to flaws and ambiguities. Subsequently, the characteristics of natural language and patterns of how it behaves in different branches of science are revealed, to indicate ways to improve the development of AI in specific fields of science. A brief description of the universal structure of language is also presented as an algorithmic model to be followed in the development of AI.

Since AI aims to imitate the process of the human mind, the book shows how the cross-fertilization between natural language and AI should be done using the logical-axiomatic structure of natural language adjusted to the logical-mathematical processes of the machine.