Βελτιστοποίηση της λήψης αποφάσεων με τη χρήση της τεχνητής νοημοσύνης. Σύγκριση κορυφαίων μοντέλων τεχνητής νοημοσύνης
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Keywords
Τεχνητή νοημοσύνη ; Λήψη αποφάσεων ; Βελτιστοποίηση ; Μοντέλα τεχνητής νοημοσύνηςAbstract
This thesis focuses on the optimization of the decision-making process in business using artificial intelligence and the comparative analysis of leading models. Initially, the importance of optimization in decision making in the business environment is discussed and the role of artificial intelligence in decision making is also discussed.
The paper continues with the theoretical foundation of the concept of artificial intelligence, examining its historical development, its main characteristics and its importance in decision making. In addition, the ChatGPT model is mentioned, the implications of artificial intelligence and its application in robotics are analysed. It also provides an analysis on the basic principles of decision making. This is followed by a detailed presentation of the leading models of artificial intelligence, such as machine learning systems, neural networks, evolutionary algorithms and rule-based systems, accompanied by an in-depth discussion of the strengths and weaknesses of each.
The application of these methods for optimizing decision making is then discussed, with particular emphasis on optimization algorithms such as genetic algorithms, particle swarm algorithms and simulated annealing.
Finally, it focuses on the comparison and evaluation of leading AI models, based on criteria such as performance and accuracy, generalizability and addressing overfitting, interpretability and transparency, fairness and non-discrimination, and reliability and robustness. It is further emphasised that there is no single perfect model for every problem, and that the choice of the appropriate algorithm depends on the characteristics of the application and the user's priorities.