==== Tutorials =====

^   T^     Date^ Tutor  ^  Contents   ^  Materials   ^    
|   1|    18.2.| JB | Introduction, entrance test, logic revision  | {{ :courses:smu:smu_entrance_test.pdf |Entrance test}}{{ :courses:smu:introtestsolution.pdf |Solution}} |
|   2|    25.2.| JB | Learning conjunctions, probabilities | {{ :courses:smu:tutorial3.pdf|Learning conjunctions}} {{ :courses:smu:tutorial2exercises.pdf |Exercises}} {{ :courses:smu:generalization_algorithm.pdf |}}|
|   3|     4.3.| JB | Mistake bounds; Assignment 1 | {{ :courses:smu:assignment1.zip |}}  {{ :courses:smu:assignment1.pdf |}} |
|   4|    11.3.| MS | Learning from interpretations | {{:courses:smu:ilp1_2019.pdf|Learning from interpretations }}  |
|   5|    18.3.| MS | LGG | {{:courses:smu:ilp2_2019.pdf|Learning from entailment}} |
|   6|    25.3.| MS | RLGG, ILP assignment | {{:courses:smu:ilp3_2019.pdf|HW assignment}} {{:courses:smu:ilpassignment2.zip|code}} |
|   7|     1.4.| PR   | Reinforcement learning   | {{ :courses:smu:rl_mdp_refreshment.pdf |slides}}, {{ :courses:smu:project3.pdf |HW assignment}}, {{ :courses:smu:project3.zip |code}} |
|   8|     8.4.| PR   | Reinforcement learning    | {{courses:smu:tutorials:rltutorial2.zip|zip}}, {{courses:smu:tutorials:rltutorial3.pdf|slides}} |
|   9|    15.4.| PR   | Reinforcement learning   | [[courses:smu:tutorials:tutorial9|Problems]], {{courses:smu:tutorials:convergence.pdf|slides}} |
|   -|    22.4 | OH    | // Easter Monday // | Bayesian networks |
|  10| 29.4.| OH   | Bayesian networks     | holiday on 1. 5. |
|  11| 6.5.| OH | Bayesian networks   | HW DLs, lab 8. 5. moved to 9. 5. |
|  12|    13.5.| TBD   | PP / PLP  | lab 15. 5. moved to 14. 5., [[https://dtai.cs.kuleuven.be/problog/tutorial.html]] |
|  13|    20.5.| TBD   | Assignment's solutions   |   |