Martin Schweizer: Catalogue data in Autumn Semester 2021 |
| Name | Prof. Dr. Martin Schweizer |
| Field | Mathematik |
| Address | Professur für Mathematik ETH Zürich, HG G 51.2 Rämistrasse 101 8092 Zürich SWITZERLAND |
| Telephone | +41 44 632 33 51 |
| Fax | +41 44 632 14 74 |
| martin.schweizer@math.ethz.ch | |
| URL | http://www.math.ethz.ch/~mschweiz |
| Department | Mathematics |
| Relationship | Full Professor |
| Number | Title | ECTS | Hours | Lecturers | |
|---|---|---|---|---|---|
| 401-3910-71L | Student Seminar on Reinforcement Learning   Number of participants limited to 12. | 4 credits | 2S | M. Schweizer | |
| Abstract | The aim of this seminar is to give an introduction to some of the mathematical ideas behind reinforcement learning. This includes stochastic optimisation and convergence analysis. The emphasis is on mathematical theory, not on developing and testing algorithms. | ||||
| Learning objective | The aim of this seminar is to give an introduction to some of the mathematical ideas behind reinforcement learning. This includes stochastic optimisation and convergence analysis. The emphasis is on mathematical theory, not on developing and testing algorithms. | ||||
| Content | The aim of this seminar is to give an introduction to some of the mathematical ideas behind reinforcement learning. This includes stochastic optimisation and convergence analysis. The emphasis is on mathematical theory, not on developing and testing algorithms. | ||||
| Literature | See the seminar homepage at https://metaphor.ethz.ch/x/2021/hs/401-3910-71L | ||||
| Prerequisites / Notice | The underlying textbook mostly works with stochastic control problems for discrete-time Markov chains with a finite state space. But for a proper understanding, students should be familiar with measure-theoretic probability theory as well as stochastic processes in discrete time, and in particular with the construction of Markov chains on the canonical path space via the Ionescu-Tulcea theorem. | ||||
| 401-5910-00L | Talks in Financial and Insurance Mathematics | 0 credits | 1K | B. Acciaio, P. Cheridito, D. Possamaï, M. Schweizer, J. Teichmann, M. V. Wüthrich | |
| Abstract | Research colloquium | ||||
| Learning objective | |||||
| Content | Regular research talks on various topics in mathematical finance and actuarial mathematics | ||||