====== Lectures ======
AIMA and AIMA3 mean the 2nd and 3rd, respectively, edition of Russel, Norvig: Artificial Intelligence- Modern Approach.

^  W ^ Date   ^ Who     ^ Topic ^
|  1. | 23.02. | P.Pošík | {{:courses:ae3m33ui:lectures:ui_robotics_ml-slides.pdf|The relations of AI, ML, and robotics}} ({{:courses:ae3m33ui:lectures:ui_robotics_ml-handouts.pdf|handouts}}). {{:courses:ae3m33ui:lectures:pr_bayes_nonbayes-slides.pdf|Pattern recognition, Bayesian and non-Bayesian tasks}} ({{:courses:ae3m33ui:lectures:pr_bayes_nonbayes-handouts.pdf|handouts}}). |
|  2. | 01.03. | P.Pošík | {{:courses:ae3m33ui:lectures:learning-slides.pdf|Learning}} ({{:courses:ae3m33ui:lectures:learning-handouts.pdf|handouts}}). {{:courses:ae3m33ui:lectures:linreg-slides.pdf|Linear regression}} ({{:courses:ae3m33ui:lectures:linreg-handouts.pdf|handouts}}). |
|  3. | 08.03. | P.Pošík | {{:courses:ae3m33ui:lectures:linclass-slides.pdf|Linear classification models. Logistic regression. Perceptron.}} ({{:courses:ae3m33ui:lectures:linclass-handouts.pdf|Handouts}}) {{:courses:ae3m33ui:lectures:svm-slides.pdf|Optimal separating hyperplane. Basis expansion. Support vector machine.}} ({{:courses:ae3m33ui:lectures:svm-handouts.pdf|Handouts}}) |
|  4. | 15.03. | P.Pošík | {{:courses:ae3m33ui:lectures:dectrees-slides.pdf|Decision trees}} ({{:courses:ae3m33ui:lectures:dectrees-handouts.pdf|handouts}}). |
|  5. | 22.03. | P.Pošík | {{:courses:ae3m33ui:lectures:biasvariance-slides.pdf|Bias-variance trade-off. Crossvalidation. Regularization.}} ({{:courses:ae3m33ui:lectures:biasvariance-handouts.pdf|Handouts}}.) |                                                      
|  6. | 29.03. | P.Pošík | {{:courses:ae3m33ui:lectures:adaboost-slides.pdf|Adaboost}} ({{:courses:ae3m33ui:lectures:adaboost-handouts.pdf|handouts}}). {{:courses:ae3m33ui:lectures:featureselectionshort-slides.pdf|Feature selection and extraction.}} ({{:courses:ae3m33ui:lectures:featureselectionshort-handouts.pdf|Handouts.}}) |                                                                                                                            
|  7. | 05.04. | P.Pošík | {{:courses:ae3m33ui:lectures:colt_en-slides.pdf|Theory of learning, problems of consistency, capacity, PAC.}} ({{:courses:ae3m33ui:lectures:colt_en-handouts.pdf|Handouts}}.) |
|  8. | 12.04. | P.Pošík | {{:courses:ae3m33ui:lectures:seqanal-slides_en.pdf|Sequential pattern recognition, Wald's algorithm}} ({{:courses:ae3m33ui:lectures:seqanal-handouts_en.pdf|Handouts}}). {{:courses:ae3m33ui:lectures:alife-slides_en.pdf|Artificial life, principles, algorithms, applications}} ({{:courses:ae3m33ui:lectures:alife-handouts_en.pdf|handouts}}). | 
|  9. | 19.04. | R.Mařík | {{:courses:ae3m33ui:lectures:p08.htnplanning.pdf|HTN}} |                  
| 10. | 26.04. | R.Mařík | {{:courses:ae3m33ui:lectures:p09.scheduling.pdf|Scheduling}} |
| 11. | 03.05. | R.Mařík | {{:courses:a3m33ui:prednasky:ui10_intelligentagents.pdf|Inteligent agents}}{{:courses:a3m33ui:prednasky:ui10_decisiontheory.pdf|Decision theory}} |
| 12. | 10.05. | R.Mařík | {{:courses:a3m33ui:prednasky:ui11_markovdecisionprocesses.pdf|Sequential decision making / Markov decision processes, value iteration, strategy iteration}}. |
| 13. | 17.05. | R.Mařík | {{:courses:a3m33ui:prednasky:ui12-reinforcementlearning.pdf|Reinforcement learning: problem formulation, exploration vs. exploitation, bandit problems, sequential learning}}. |
| 14. | 24.05. | R.Mařík | {{:courses:a3m33ui:prednasky:files:ui-2010-p12-agent_oriented_programming.pdf|Agent oriented programming: reactive planning, BDI architecture, AgentSpeak, Jason}}. |

See also [[courses:ae3m33ui:other_sources|other sources]]!