==== Lectures =====
<fc #ff0000>Lecture 11 slides updated on May 18</fc>. 

The lectures are given in English to all students. **Lecture slides up to the latest lecture: {{courses:smu:smu-slides.pdf}}.**

The book links below pointing to Springer Link let you download the PDFs if accessing from the CVUT domain. Don't get confused by the indexing in the Universal AI book: it is different from ours because Hutter assumes the agent-env interaction to start with an agent's action whereas we start with a percept from the environment (for us, this is more natural in the reinforcement and concept learning scenarios).

^ Lec # ^ Lecture date ^ Slides available ^ Online Meeting ^ (Planned) Contents  ^  Additional Reading ^
|  1|  17.2|  17.2| | General framework, passive reinforcement learning, DUE and ADP agents  | [[http://aima.cs.berkeley.edu|AIMA book]] Chapter 21, [[http://incompleteideas.net/book/bookdraft2018jan1.pdf|RL Book]] |
|  2|  24.2|  24.2| | TD agent, active R/L, Q-learning | as above   |
|   |   2.3|   | | (school closed) | 
|  3|   9.3|  9.3| | SARSA agent, state representation, policy search,  Bayesian approach  | as above (except Bayesian)  |
|  4|   |  23.3 |  30.3 16:15| Finish Bayesian approach. Universal sequence prediction, AIXI agent; Intro to concept learning. |[[https://link.springer.com/book/10.1007/b138233|Universal AI Book]] Chapter 1 (optionally other chapters for deeper understanding); [[http://hutter1.net/ai/uaibook.htm|supplementary web]]   |
|  5|  |  30.3|  6.4 16:15| Online concept learning, mistake-bound model |numerous sources [[https://en.wikipedia.org/wiki/Computational_learning_theory|here]] |
|  6|  |  6.4|  <fc #ff0000>13.4 16:15</fc>| Batch-learning, PAC-learning model  |as above  |
|  7|  |  17.4|  20.4. 16:15| Finish PAC-learning. Learning relational concepts  |[[https://link.springer.com/book/10.1007/3-540-62927-0|ILP Book]], [[https://link.springer.com/book/10.1007/978-3-540-68856-3|Logical Learning Book]] |
|  8|  |  26.4|  27.4 16:15|Reduction, Learning with Background Knowledge |as above |
|  9|  |  4.5|  4.5 16:15| Functions, Inductive Logic Programming, Structured Output | as above + [[http://aima.cs.berkeley.edu|AIMA book]] Ch. 9.4.2 and 19.5; [[https://en.wikipedia.org/wiki/Inductive_logic_programming|ILP wiki]] | 
|  10| |  11.5|  11.5 16:15| Bayesian networks - Conditional independence, Inference |[[http://aima.cs.berkeley.edu|AIMA book]] Ch. 14  |
|  11| |  18.5|  18.5 16:15| Bayesian networks - MAP inference, parameter learning | [[http://aima.cs.berkeley.edu|AIMA book]] Ch. 20.2.4 (MAP Inference not in AIMA) |
|  | |  |   | <del>Learning with queries</del> |   |

**Consultations:** please ask your questions in the [[https://cw.felk.cvut.cz/forum/forum-1633-page-1.html|forum]] and/or at the online meeting.