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| Anno Accademico |
2025/2026 |
| Corso di Studi |
Dott. - MI (1380) Ingegneria dell'Informazione / Information Technology |
| Anno di Corso |
1 |
| Codice Identificativo |
063925 |
| Denominazione Insegnamento |
STOCHASTIC DYNAMIC PROGRAMMING |
| Tipo Insegnamento |
MONODISCIPLINARE |
| Crediti Formativi Universitari (CFU) |
5.0 |
| Programma sintetico |
The course focuses on sequential decision-making in the face of uncertainty. A variety of real-world challenges fall within this scope, including problems in business, engineering, the sciences, and health care. In such problems, the decision-maker is tasked with identifying alternatives that perform well not only now, but across some horizon. Because sequential decision problems cut across many domains, they are studied in various disciplines. The engineering community focuses on optimal control, the operations research community references Markov decision processes, and the computer science community studies reinforcement learning. In this course, we leverage advances in each of these communities to study stochastic dynamic programs (SDPs). We address modeling, policy creation, and the development of dual bounds for SDPs. The course will be of particular interest to students who want to connect deterministic optimization techniques with SDP solution strategies. |
| Settori Scientifico Disciplinari (SSD) |
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Codice SSD
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Descrizione SSD
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CFU
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MAT/06
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PROBABILITA' E STATISTICA MATEMATICA
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5.0
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Scaglione
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Nome
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Programma dettagliato
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Da (compreso)
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A (escluso)
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A
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ZZZZ
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Jabali Ola, Goodson Justin Christopher
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