Resumen de Quality data for optimum research vs sustainable corporate development
Vítor Manuel Da Silva Alves
This doctoral proposal is in line with the UNESCO (2019), United Nations guidelines of Artificial Intelligence (AI) for sustainable development for sustainable cities of the future. In the last years, many studies have been published using AI techniques in smart cities and sustainability domains, for example in Healthcare, Social Behavior, Organizational Performance and Urban Safety. Following previous work, additional research in the field of Digital Transformation for Sustainable Systems using AI algorithms have been studied and accepted to be published. In this context and exploring the relationship between Artificial Intelligence/Machine Learning, Digital Transformation and Sustainable environments for Smart Cities, this doctoral proposal presents an approach to the modulation of creative evolutive systems that materializes the knowledge representation and reasoning processes in terms of the Laws of Thermodynamics. We intent to create a global computational framework based on symbolic, evolutionary and connectionist approaches for sustainable cities. Under the Extended Logic Programming paradigm for knowledge representation and reasoning using the evolutionary programming paradigm, the candidate solutions are seen as evolutionary logic programs or theories, being the test whether a solution is optimal based on a measure of the quality-of-information seen as an entropic state materialized as untainted energy which ranges in the interval [0,1] and, according to the First Law of Thermodynamics. With the modulation of these type of systems, we be able to build a dynamic virtual world of complex and interacting entities, here materialized as evolutionary programs, and consequently the superlative modulation of the system for the problem in observation. In this way, the proposed work is in line with UNESCO (2019) in fostering quality data for optimum research, ensuring quality data and data management.
