Lecture 1st hour 2nd hour Material/chapter generally:
R & N (chapter+page numbers as in 1st edition) plus lecture slides
1 Planning (LS) idem Ch. 11-13, pp. 337-412 Planning + slides
2 Knowledge-based symbolic methods Example geometric modelling & matching (MB) Ch. 19.6, pp. 588-597, Ch. 21, pp. 625-648 Bayes & knowledge + slides 1,2
3 Static symbolic methods (LS) Example spamfilter(MB)
Computational Learning Theory (MB)

Ch. 17, pp. 498-522 Making complex decisions, + POMPD slides Game of Hearts
Ch. 18.6 pp. 552-555 (until and not including "Learning decision lists") + PAC slides

4 Heterogenous-Information-Integration Example writer identification PPT slides on Borda rank combination
5 Decision trees Assignment Ch. 18.3 pp. 531-544 Learning Decision Trees + article
6 Grammar Induction Articles Ch. 22, pp. 651-690 + artikel Guyon
7 Misc. Topics Hidden Markov models (MB) Rabiner paper pp.257-266 (until
and not including "Types of HMMs")
HMM slides 
jan (exam)