110 http://isa.epfl.ch/imoniteur_ISAP/ itffichecours.txt?path=EPFL.Etu.FicheCours.HeaderFR itffichecours.txt?path=EPFL.Etu.FicheCours.GlobalNav_js fr 2026 32211080 32211080 2305107546 2305107546 1 0 Management de la technologie (edoc) EDMT !itffichecours.htm?ww_i_matiere=352617902&ww_x_anneeAcad=2305107546&ww_i_section=32211080&ww_i_niveau= 1696552884 1696552963 2024-2025 COURSE BOOKLET MGT-484 Applied probability & stochastic processes Applied probability & stochastic processes Lecturers Cristi Andrés Language of teaching English Cursus Life Sciences Engineering(2024-2025, SV - Master 2023)
Life Sciences Engineering(2024-2025, SV - Master 2024)
Management of technology (edoc)(2024-2025, EDMT 2024-25)
Management, Technology and Entrepreneurship minor(2024-2025, Mineur : Management de la technologie et entrepreneuriat 2024-25)
Management, Technology and Entrepreneurship(2024-2025, MTEE - Master 2023)
Management, Technology and Entrepreneurship(2024-2025, MTEE - Master 2024)
Neuro-X minor(2024-2025, Mineur : Neuro-X 2024-25)
Neuro-X(2024-2025, SNX - Master 2023)
Neuro-X(2024-2025, SNX - Master 2024)
Physics of living systems minor(2024-2025, Mineur : Physique des systèmes vivants 2024-25)
Systems Engineering minor(2024-2025, Mineur : Systems Engineering 2024-25)
SemesterMand.OptionFilières
x
Hx
MA1, MA3x
MA1, MA3x
 Credits 4 Session Winter Workload 120h Exam Written Number of positions Semester Fall Weeks 14 Hours 4 weekly
Courses 2 weekly
Exercises 2 weekly
Study planSemesterMand.OptionFilières
EDMT - Management of Technology 2024-25x
Ingénierie des sciences du vivant 2024-25MA1x
Ingénierie des sciences du vivant 2024-25MA3x
Management, technologie et entrepreneuriat 2024-25MA1x
Management, technologie et entrepreneuriat 2024-25MA3x
Mineur : Management, technologie et entrepreneuriat 2024-25Hx
Mineur : Neuro-X 2024-25Hx
Mineur : Physique des systèmes vivants 2024-25Hx
Mineur : Systems engineering 2024-25Hx
Neuro-X 2024-25MA1x
Neuro-X 2024-25MA3x
Cursus Sem. Type
Life Sciences Engineering MA1, MA3 Opt.
Management of technology Opt.
Management, Technology and Entrepreneurship minor H Opt.
Managmt, tech et entr. MA1, MA3 Obl.
Neuro-X minor H Opt.
Neuro-X MA1, MA3 Opt.
Physics of living systems minor H Opt.
Systems Engineering minor H Opt.
Summary This course focuses on dynamic models of random phenomena, and in particular, the most popular classes of such models: Markov chains and Markov decision processes. We will also study applications in queuing theory, finance, project management, etc. Content Keywords

Markov chains, Markov decision processes, dynamic programming, optimal control

 Learning Outcomes By the end of the course, the student must be able to:
  • Formulate Markov chain models for dynamic uncertain phenomena.
  • Formulate Markov decision process models for dynamic decision problems under uncertainty.
  • Use these models to structure real decision-making situations.
  • Compute relevant performance measures for Markov models.
  • Develop an awareness of the manifold uses of probability theory in management science.
  • Reason about the concept of a discrete-time Markov chain and understand how Markov chains are used to model random phenomena
  • Compute several properties of a given Markov chain, such as hitting probabilities, expected hitting times, invariant distributions and the long-run proportion of time spent in a given state
  • Formalize decision problems under uncertainty as optimal control models
  • Solve optimal control models via dynamic programming
  • Analyze the technical literature in applied probability and to undertake independent self-study (or research) in the future
 Transversal skills
  • Communicate effectively, being understood, including across different languages and cultures.
  • Assess one's own level of skill acquisition, and plan their on-going learning goals.
  • Use a work methodology appropriate to the task.
  • Demonstrate the capacity for critical thinking
 Teaching methods

Classical formal teaching interlaced with practical exercices.

 Expected student activities

Active participation in exercise sessions is essential.

 Assessment methods
  • 30% midterm exam
  • 70% final exam
 Resources Bibliography

Introduction to Probability Models, 10th edition, Sheldon M. Ross, Academic Press, 2009.

Dynamic Programming and Optimal Control, 3rd edition, Dimitri P. Bertsekas, Athena Scientific, 2005.

Introduction to Probability, Dimitri P. Bertsekas and John N. Tsitsiklis, Athena Scientific, 2002.

 

 

 Ressources en bibliothèque
  • Introduction to Probability Models, 10th edition, Sheldon M. Rosshttp://library.epfl.ch/en/beast?isbn=9780123756862
  • Dynamic Programming and Optimal Control, 3rd edition, Dimitri P. Bertsekashttp://library.epfl.ch/en/beast?isbn=1886529264
  • Introduction to Probability, Dimitri P. Bertsekas and John N. Tsitsiklishttp://library.epfl.ch/en/beast?isbn=9781886529236
 Moodle Link Prerequisite for

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FO_fin HTML_debut &#966; HTML_fin JS_debut \x26#966; JS_fin CODE68199285 BOOLEAN_Symbol 1 BaliseJS_debut \x5bPHI\x5d BaliseJS_fin Balise_debut [PHI] Balise_fin FO_debut [inline]=&#934; FO_fin HTML_debut &#934; HTML_fin JS_debut \x26#934; JS_fin CODE68199991 BOOLEAN_Symbol 1 BaliseJS_debut \x5bgamma\x5d BaliseJS_fin Balise_debut [gamma] Balise_fin FO_debut [inline]=&#947; FO_fin HTML_debut &#947; HTML_fin JS_debut \x26#947; JS_fin CODE68200031 BOOLEAN_Symbol 1 BaliseJS_debut \x5bGAMMA\x5d BaliseJS_fin Balise_debut [GAMMA] Balise_fin FO_debut [inline]=&#915; FO_fin HTML_debut &#915; HTML_fin JS_debut \x26#915; JS_fin CODE68200077 BOOLEAN_Symbol 1 BaliseJS_debut \x5bomega\x5d BaliseJS_fin Balise_debut [omega] Balise_fin FO_debut [inline]=&#969; FO_fin HTML_debut &#969; HTML_fin JS_debut \x26#969; JS_fin CODE68200150 BOOLEAN_Symbol 1 BaliseJS_debut \x5bOMEGA\x5d BaliseJS_fin Balise_debut [OMEGA] Balise_fin FO_debut [inline]=&#937; FO_fin HTML_debut &#937; HTML_fin JS_debut \x26#937; JS_fin CODE72092691 BOOLEAN_Symbol BaliseJS_debut \x5beta\x5d BaliseJS_fin Balise_debut [eta] Balise_fin FO_debut [inline]=&#951; FO_fin HTML_debut &#951; HTML_fin JS_debut \x26#951; JS_fin CODE72092805 BOOLEAN_Symbol BaliseJS_debut \x5bETA\x5d BaliseJS_fin Balise_debut [ETA] Balise_fin FO_debut [inline]=&#919; FO_fin HTML_debut &#919; HTML_fin JS_debut \x26#919; JS_fin BALISE_SOULIGNER BOOLEAN_Symbol BaliseJS_debut \x5bu\x5d BaliseJS_fin \x5b\x2fu\x5d Balise_debut [u] Balise_fin [/u] FO_debut text-decoration=underline FO_fin text-decoration=none HTML_debut <u> HTML_fin </u> JS_debut \x3cu\x3e JS_fin \x3c\x2fu\x3e CODE72092388 BOOLEAN_Symbol BaliseJS_debut \x5bpsi\x5d BaliseJS_fin Balise_debut [psi] Balise_fin FO_debut [inline]=&#968; FO_fin HTML_debut &#968; HTML_fin JS_debut \x26#968; JS_fin CODE72092541 BOOLEAN_Symbol BaliseJS_debut \x5bPSI\x5d BaliseJS_fin Balise_debut [PSI] Balise_fin FO_debut [inline]=&#936; FO_fin HTML_debut &#936; HTML_fin JS_debut \x26#936; JS_fin CODE140502511 BOOLEAN_Symbol 1 BaliseJS_debut \x5brho\x5d BaliseJS_fin Balise_debut [rho] Balise_fin FO_debut [inline]=&#961; FO_fin HTML_debut &#961; HTML_fin JS_debut \x26#961; JS_fin CODE140504636 BOOLEAN_Symbol 1 BaliseJS_debut \x5bRHO\x5d BaliseJS_fin Balise_debut [RHO] Balise_fin FO_debut [inline]=&#929; FO_fin HTML_debut &#929; HTML_fin JS_debut \x26#929; JS_fin CODE148292791 BOOLEAN_Symbol BaliseJS_debut \x5bepsilon\x5d BaliseJS_fin Balise_debut [epsilon] Balise_fin FO_debut [inline]=&#949; FO_fin HTML_debut &#949; HTML_fin JS_debut \x26#949; JS_fin CODE169976220 BOOLEAN_Symbol BaliseJS_debut \x5blig\x5d BaliseJS_fin Balise_debut [lig] Balise_fin FO_debut [inline]=&#x203A;&#160;&#160; FO_fin HTML_debut &#x203A;&#160;&#160; HTML_fin JS_debut \x26#x203A;\x26#160;\x26#160; JS_fin CODE148292899 BOOLEAN_Symbol BaliseJS_debut \x5bEPSILON\x5d BaliseJS_fin Balise_debut [EPSILON] Balise_fin FO_debut [inline]=&#917; FO_fin HTML_debut &#917; HTML_fin JS_debut \x26#917; JS_fin BALISETXT_SAUT BOOLEAN_Symbol BaliseJS_debut \x5bbr\x2f\x5d BaliseJS_fin Balise_debut [br/] Balise_fin FO_debut FO_fin HTML_debut <br/> HTML_fin JS_debut \x3cbr\x2f\x3e JS_fin 352617902 Applied probability & stochastic processes Applied probability & stochastic processes anglais Cristi Espinosa Andrés Ignacio 367834 32211080