Week #

Monday 
Wednesday 
Friday 
1 
Sept
28: (no classes yet) 
Sept
30: Lecture (in EEB 045). Course introduction, definition of intelligence, Turing Test. Assignment 1 (Symbol manipulation in Python) given out.

Oct
2: Lab (in MGH 030). Introduction to Python; interaction; function definition and calling; lists;

2

Oct
5: Lecture (in EEB 045). Python functions; recursive functions on lists; lambda expressions; mapping; string operations. Example: Sequence prediction.

Oct
7: Lecture (in EEB 045). Statespace search: Introduction. Assignment 1 due; Assignment 2 (Statespace search) given out.

Oct
9: Lab (in MGH 030). Game playing.

3

Oct
12: Lecture (in EEB 045). Statespace search: Theory and algorithms.

Oct
14: Lecture (in EEB 045). Statespace search: Posing problems for statespace search.

Oct
16: Lab (in MGH 030). Interactive StateSpace Search. Assignment 2 due. Assignment 3 (Game playing) given out.

4

Oct
19: Lecture (in EEB 045). Statespace search (conclusion).

Oct
21: Quiz (in EEB 045) on statespace search 
Oct
23: Lecture (in EEB 045). Followup to the quiz.

5

Oct
26: Class interrupted by fire alarm. Assignment 3 due. Assignment 4 (Logical reasoning) given out.

Oct
28: Lecture (in EEB 045). Knowledge representation with ISA hierarchies.

Oct
30: Lecture (in EEB 045). Propositional logic, modus ponens, perfect induction, and resolution.

6

Nov
2: Lecture (in EEB 045). Predicate logic. Definitions. Hornclause resolution and unification.

Nov
4: Lecture (in EEB 045). Predicate logic, continued. Logical encoding. Assignment 4 due.

Nov
6: Lecture (in EEB 045). Interpretations, models, satisfiability.

7

Nov
9: Lecture (in EEB 045). Logic programming and expert systems using Horn clause resolution in PROLOG.

Nov
11: Veterans Day Holiday (no class) 
Nov
13: Lecture (in EEB 045). Probabilistic inference with Bayes' rule. Bayes' networks.

8

Nov
16: Midterm exam (in EEB 045) 
Nov
18: Project planning (in EEB 045)

Nov
20: Lab (in MGH 030). Experiments in image understanding.

9

Nov
23: Lecture (in EEB 045). Information about project options: the Bayes Net Toolkit, CoSolve.

Nov
25: Lecture (in EEB 045). Image understanding: sampling and quantization, histograms, thresholding, edge detection, segmentation into regions; morphology.

Nov
27: Day after Thanksgiving: no class 
10

Nov
30: Lecture (in EEB 045). Image understanding: the Hough transform, scene labeling, pattern recognition with perceptrons. Assignment 5 given out (Probabilistic reasoning and image understanding).

Dec
2: Lecture (in EEB 045). Neural networks and machine learning: perceptron training and backpropagation.

Dec
4: Lecture (in EEB 045). Natural language understanding I: contextfree grammars and parsing. Semantic grammars and Semantics: Case frames.

10

Dec
7 Lecture (in EEB 045). Big issues and the future of AI: common sense, ontologies, dangers of AI, Asimov's rules of robotics, hopes for AI. Assignment 5 due.

Dec
9: Lab (in MGH 030). Presentations and Demos.

Dec
11: Lab (in MGH 030). Demos


Dec
16 (Wednesday):
Final Exam, 2:304:20 PM.
