Games and reinforcement learning
| Code | Completion | Credits | Range | Language |
|---|---|---|---|---|
| NI-GLR | Z,ZK | 4 | 2P+2C | English |
- Garant předmětu:
- Lecturer:
- Tutor:
- Supervisor:
- Department of Applied Mathematics
- Synopsis:
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The field of reinforcement learning is very hot recently, because of advances in deep learning, recurrent neural networks and general artificial intelligence. This course is intended to give you both theoretical and practical background so you can participate in related research activities.
Presented in English.
- Requirements:
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BI-ZUM - Introduction to artificial intelligence
- Syllabus of lectures:
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Algorithmic game theory
1. Sealed-bid combinatorial auctions
2. Iterative combinatorial auctions
3. Stable matching
4. Congestion games. Selfish routing and the price of anarchy
5. Potential games. Network cost-sharing games
6. Best response dynamics. No-regret dynamics.
Introduction to Reinforcement Learning
7. Multiarmed Bandit Algorithms.
8. Finite Markov Decision Processes
9. Dynamic Programming
10. Montecarlo methods
11. Temporal-Difference learning
12. Multi-step bootstrapping
13. Planning and learning with tabular methods
- Syllabus of tutorials:
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Algorithmic game theory
1. Mechanism design basics. Auctions of physical goods.
2. Sponsored search auctions (online advertising).
3. Congestion games. Selfish routing and the price of anarchy
4. Traffic assignment in networks.
5. Best response dynamics. No-regret dynamics.
6. Rock, paper, scissors.
Introduction to Reinforcement Learning
7. Multiarmed Bandit Algorithms.
8. Markov chains and MDP's.
9. Algorithms: Q-learning, TD
10. Playing tic-tac-toe, checkers.
11. Tensorflow introduction.
12. Case studies: TD-gammon, Atari games, Go playing.
13. OpenAI Gym. Policy gradient algorithm.
- Study Objective:
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Teach theoretical and practical aspects of the game theory and reinforcement learning.
- Study materials:
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Reinforcement Learning: An introduction, Sutton and Barto, 2nd edition draft, 2017.
Algorithmic Game Theory, Roughgarden, Tardos, Vazirani and Nisan, 2007.
- Note:
- Further information:
- No time-table has been prepared for this course
- The course is a part of the following study plans:
-
- Master specialization Computer Security, in Czech, 2020 (elective course)
- Master specialization Design and Programming of Embedded Systems, in Czech, 2020 (elective course)
- Master specialization Computer Systems and Networks, in Czech, 202 (elective course)
- Master specialization Management Informatics, in Czech, 2020 (elective course)
- Master specialization Software Engineering, in Czech, 2020 (elective course)
- Master specialization System Programming, in Czech, version from 2020 (elective course)
- Master specialization Web Engineering, in Czech, 2020 (elective course)
- Master specialization Knowledge Engineering, in Czech, 2020 (elective course)
- Master specialization Computer Science, in Czech, 2020 (elective course)
- Mgr. programme, for the phase of study without specialisation, ver. for 2020 and higher (elective course)
- Master specialization Software Engineering, in English, 2021 (elective course)
- Master specialization Computer Security, in English, 2021 (elective course)
- Master specialization Computer Systems and Networks, in English, 2021 (elective course)
- Master specialization Design and Programming of Embedded Systems, in English, 2021 (elective course)
- Master specialization Computer Science, in English, 2021 (elective course)
- Study plan for Ukrainian refugees (elective course)
- Master Specialization Digital Business Engineering, 2023 (elective course)
- Master specialization System Programming, in Czech, version from 2023 (elective course)
- Master specialization Computer Science, in Czech, 2023 (elective course)