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UMBC CMSC 671 Fall 2020
Principles of Artificial Intelligence

Schedule

subject to change

# Day Date Topic Read 1st Slides
Video Quiz,
Homework
Seealso
1 Thr 8/27 Administrivia, Introduction, history RN1 00
01
L01 hw1 out History of AI
2 Tue 9/1 Agents
RN2

02

L02   Software agents
3 Thr 9/3 Problem solving as search
RN3
L03


Graph traversal algorithms, PHW on Search

4 Tue 9/8 Uninformed & Informed search
RN4
L04


Missionaries and cannibals, Water jugs, aima code, wj.py, wj.ipynb

5 Thr 9/10 Informed search
RN4 
L05

Search demo, A* algorithm, 8 puzzle visualization

6 Tue 9/15 Informed Search
RN4
L06


p8.py, Simulated annealing, 8 Queens problem,

7 Thr 9/17 Constraints
RN5
L07


CCC site, 8 queens CSP, csp.py, CSP demo, SLS CSP demo, Genetic algorithm

8 Tue 9/22

Constraints

RN5
L08


ms3.py, mapc.py, sudoku.py, python-constraints
9 Thr 9/24 Games
RN 6
L09

Checkers solved; U. Alberta Games Group; AlphaGo
10 Tue 9/29 Games
RN 6
L10
It, New Yorker, 1952;
11 Thr 10/1 Games Theory
RN 17.6
L11

game theory, PD demo, PD lessons, Prisoner's Dilema, Chicken, Evolution of Trust

12 Tue 10/6 Reasoning Agents
RN7
L12   Hunt the Wumpus; neats vs scruffies
13 Thr 10/8 Reasoning Agents
RN7
L13   Knowledge Base; Wason selection task;
14 Tue 10/13

MIDTERM EXAM

 
   

material thru 10/1, 75 minute exam held online between 1 and 3

15 Thr 10/15 KR and FOL
RN8
L14

see notes 9.3.1 and 9.3.2
16 Tue 10/20 FOL RN9 09 L15   see notes 9.3.2 and 9.4.1
17 Thr 10/22 Knowledge representation
RN10
L16 hw4 out  
18 Tue 10/24

Planning

RN11
13
L17   STRIPS, Planning and scheduling
19 Thr 10/29 Planning & Bayes
RN11, RN12
13, 15 L18

PDDL, Bayes theorem video

20 Tue 11/3 no class
--
--
-- -- --
21 Thr 11/5 Bayesian Networks
RN13
15
L19

hw4 due
hw5 out

Netica BBN Tutorial
22 Tue 11/10 Machine Learning RN19
video
14 L20

 

Google's Rules of Machine Learning, Unreasonable Effectiveness of Data
23 Thr 11/12 Decision trees

RN19

L21  

Decision tree learning, weka, scikit-learn

24 Tue 11/17 Decision trees, SVMs, tools
RN19
video
L22 hw5 due Support vector machine
25 Thr 11/19 methodology, clustering
RN19
L23 hw6 out Training, validation, test sets, Precision and recall, FI, Cluster analysis, colab notebooks
26 Tue 11/24 hierarchical clustering, bagging
RN19
L24   hierarchical clustering, ensemble learning, colab clustering notebooks
-- Thr 11/26 --
--
--
  -- --
27 Tue 12/1 neural networks RN21
14_01 L25   colab notebooks, NN playground
28 Thr 12/2 neural networks RN21 14_02 L26 hw6 due colab notebooks, keras.io
29 Tue 12/8 deep learning, wrap up RN21 14_03 L27   word2vec demo
-- Wed 12/9 -- -- --      
--
Tue

12/15, 1-3pm

FINAL EXAM
see
above
see
above
    old exams