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Presentation
Presentation
The CU of Mathematics II develops fundamental skills of Mathematics applied to Business Intelligence and Economic Intelligence, following a method of teaching based on problems from Economics, Corporate Management in general and Aeronautical Management in particular. Skills are developed in the application of mathematical methods to scenario analysis, risk analysis and strategic foresight aimed at resilience and sustainability solutions in the context of Economics and Corporate Management.
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Class from course
Class from course
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Degree | Semesters | ECTS
Degree | Semesters | ECTS
Bachelor | Semestral | 5
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Year | Nature | Language
Year | Nature | Language
1 | Mandatory | Português
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Code
Code
ULHT1656-505
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Prerequisites and corequisites
Prerequisites and corequisites
Not applicable
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Professional Internship
Professional Internship
Não
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Syllabus
Syllabus
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 CP.2.3. Evolutionary Modeling and Chaos Theory SP.3. Generative Artificial Intelligence and Game Theory CP.3.1. Mathematica 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
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Objectives
Objectives
LO1. To know how to apply the main methods and techniques of Mathematics applied to Business Intelligence and Economic Intelligence in the context of support to decision making in Economics and Management. LO2. To know how to apply Game Theory to decision-making problems in Economics and Management, as a source of scenario analysis and simulation mathematical methods. LO3. Know how to apply Generative Artificial Intelligence to problems of strategic analysis in the context of Aeronautical Management.
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Teaching methodologies and assessment
Teaching methodologies and assessment
Theoretical-practical CU lectured from application examples based on real cases in the context of aeronautical management allowing students to acquire problem-solving skills and skills in the application of mathematics to strategic decision-making problems within the scope of aeronautical management, as well as expand the skills in dynamic modeling initiated in the CU of Mathematics I.
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References
References
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. Peterson, M. (2017). An Introduction to Decision Theory. Cambridge, Cambridge University Press. ISBN: 978-1316606209. Rutherford, A. (2021). Learn Game Theory: A Primer to Strategic Thinking and Advanced Decision-Making. UK, ARB Publications. ASIN: B0916P1W3K Sharda, R., Delen, D., Turban, E. (2014). Business Intelligence and Analytics - Systems for Decision Support. Global Edition. Essex, Pearson. ISBN: 978-1-292-00920-9. Gonçalves, CP (2022). Coupled Stochastic Chaos and Multifractal Turbulence in an Artificial Financial Market. International Journal of Swarm Intelligence and Evolutionary Computation, Vol. 11 Iss. 7, Forthcoming.
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Office Hours
Office Hours
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Mobility
Mobility
Yes