Class Mathematics II

The Mathematics II course unit focuses on three fundamental branches of applied mathematics: game theory, probability theory, and computational mathematics, developing essential skills in mathematics applied to Business Intelligence and Economic Intelligence. It follows a problem-based learning (PBL) approach applied to Economics, Business Management in general, and Aeronautical Management in particular. Students develop competencies in the application of mathematical methods to scenario analysis, risk analysis, and strategic foresight, aiming at solutions that promote resilience and sustainability in the context of Aeronautical Management.

Not applicable

SP.1. Mathematics Applied to Business Intelligence and Decision-Making in Economics and Management SP.1.1. Mathematical methods in the context of Business Intelligence and of Economic Intelligence SP.1.2. Probability Theory and Scenario Analytics SP.2. Fundamental Elements of Game Theory CP.2.1. Nash Equilibria in Pure and Mixed Strategies CP.2.2. Mixed Strategies and Scenario Analytics SP.3. Generative Artificial Intelligence and Game Theory CP.3.1. Mathematics of computation and Artificial Intelligence CP3.2. Artificial Intelligence and Game Theory CP.3.3. Algorithms for calculating Nash equilibria and their implementation in Python CP.3.4. Use of Generative AI in game theory applications to real cases

A theoretical-practical CU taught using application examples based on real-world cases in the context of Economics and Management in general, and Aeronautical Management in particular. It enables students to develop problem-solving skills and the application of Mathematics to strategic decision-making problems in the field of Aeronautical Management, while also expanding the modeling skills initiated in the Mathematics I course unit.

Tadelis, S. (2024). Game Theory: An Introduction (2nd ed.). Princeton University Press. ISBN: 978-0-691-24941-1 Stratis, K. (2023). What Is Generative AI? O’Reilly Media. ISBN¿978¿1098162658 Espinola-Arredondo, A., & Muñoz¿Garcia, F. (2023). Game Theory: An Introduction with Step-by-Step Examples. Palgrave Macmillan. ISBN: 978-3-031-37573-0. Aumann, R.J. (2020). Lectures On Game Theory. New York, Routledge. ISBN: 978-0367162047. Jagoda, P. (2020). Experimental Games: Critique, Play, and Design in the Age of Gamification. Chicago, University of Chicago Press. ISBN: 978-0226629971. Steinberg, A., Appugliese, C., Hake, P., & Bisson, S. (2025). Generative AI for Business. O’Reilly Media, Inc. ISBN¿979¿8341622371  Russell, S., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach (4th ed.). Pearson. ISBN: 978-0134610993