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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2020/2021

Symbolic Machine Learning

The course is not on the list Without time-table
Code Completion Credits Range Language
B4M36SMU Z,ZK 6 2P+2C Czech
The course cannot be taken simultaneously with:
Symbolic Machine Learning (BE4M36SMU)
Lecturer:
Tutor:
Supervisor:
Department of Computer Science
Synopsis:

The course will explain methods through which an intelligent agent can learn, that is, improve its behavior from observed data and background knowledge. The learning scenarios will include on-line learning and learning from i.i.d. data (along with the PAC theory of learnability), as well as the active and reinforcement learning scenarios. Symbolic knowledge representations (mainly through logic and graphs) will be used where possible. The course is given in English to all students.

Requirements:
Syllabus of lectures:

1. General framework, passive reinforcement learning

2. TD agent, active R/L, Q-learning

3. SARSA agent, state representation, policy search, AIξ agent

4. Universal sequence prediction, AIXI agent; Non-sequential concept learning.

5. Online learning, mistake-bound model

6. Batch learning, PAC-learning model

7. Learning first-order logic conjunctions

8. Learning first-order logic clauses

9. Learning with queries

10. Bayesian networks

11. Bayesian networks

12. Probabilistic (logic) programming

13. Probabilistic (logic) programming

Syllabus of tutorials:
Study Objective:
Study materials:

Lecture slides available at https://cw.fel.cvut.cz/wiki/courses/smu/start

Stuart Russell and Peter Norvig: Artificial Intelligence: A Modern Approach, Prentice Hall 2010

Luc De Raedt: Logical and Relational Learning, Springer 2008

Marcus Hutter: Universal artificial intelligence, Springer 2005

Note:
Further information:
https://cw.fel.cvut.cz/b192/courses/smu/start
No time-table has been prepared for this course
The course is a part of the following study plans:
Data valid to 2020-09-22
For updated information see http://bilakniha.cvut.cz/en/predmet4701606.html