CPSC 522 - AI 2
Schedule

Here is a tentative schedule. The dates for all topics in the future should be regarded as fiction.

• Jan 4 - Intro to AI, Design space of AI, knowledge representation. Reading: AIFCA Chapter 1.
• Jan 6 - Control, Hierarchical Control. Reading: AIFCA Chapter 2. Assignment 0 Due on Friday.
• Jan 11 - Probability. Belief networks and Independence. See Bayes net tool used in class.
• Jan 13 - Probabilistic Inference.
• Jan 18 - Markov Chains, localization demo, Monte Carlo methods, Sebastian Thrun's Animation of Monte Carlo Localization using laser range finders from Thrun's videos.
• Jan 20 - Learning Overview, Trivial Learning, .
• Jan 25 - Learning Probabilities, Learning Conditional Probabilities, Unsupervised Learning , Learning Bayesian Networks, Bayesian Learning .
• Jan 27 - Utilities.
• Feb 1 - utilities (cont.), Decisions.
• Feb 3 - decisions (cont.), Processes.
• Feb 10 - reinforcement learning Reinforcement Learning.
• Feb 22 - reinforcement learning (cont) and Relational Probabilistic Models.
• Feb 24 - Relational Logic.
• Feb 29 - relational logic (cont) and Variables, Negation as failure. The code examples were from ailog2.
• March 2 - Proofs.
• March 7, 9, 14 - Presentations
• March 16 - expressiveness of various representations. Collaborative filtering, Code: relnCollFilt522.py, cs522.py, u.data
• March 21 - collaborative filtering (cont). Lifted Inference
• March 23 - lifted inference (cont.)
• March 30 - Triples, Ontologies and OWL
• April 4 - putting it together semantic science.
• April 6 - Review,

Last updated: 2016-03-01, David Poole