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UMBC CMSC 471.02 Spring 2023
Introduction to Artificial Intelligence

Schedule

subject to change

# Day Date Topic Read Slides
Video Homework See also
1 Tue 1/31 Administrivia, Introduction, AI history RN1 00
01
L01 hw1 out History of AI
2 Thr 2/2 Agents
RN2

02

L02   Software agents
3 Tue 2/7 Problem solving as search
RN3
L03


Graph traversal algorithms, PHW on Search

4 Thr 2/9 Uninformed search
RN4
L04

hw1 due

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

5 Tue 2/14 Informed search
RN4 
L05
hw1 check

Search demo, A* algorithm,

6 Thr 2/16 Informed Search
RN4
L06

HW2 out

8 puzzle visualization, p8.py, 8 Queens problem,

7 Tue 2/21 Local Search
RN4
L07


Hill Climbing, Simulated annealing, Genetic algorithm, Tabu Search

8 Thr 2/23 Constraints
RN6
L08

 

CCC site, 8 queens CSP, csp.py, CSP demo, SLS CSP demo
9 Tue 2/28 Constraints
RN 6
L09

ms3.py, mapc.py, sudoku.py, python-constraints
10 Thr 3/2 Games
RN 5
L10

hw2 due
hw3 out

It, New Yorker, 1952; Checkers solved; U. Alberta Games Group; AlphaGo
11 Tue 3/7 Games and Game Theory

RN 5, 18.2

L11

game theory, Prisoner's Dilemma, Chicken, Evolution of Trust

12 Thr 3/9 Game Theory
RN18.2
L12   PD demo, PD lessons, Axelrod, Colab notebooks
13 Tue 3/14 no power, no class
--
-- hw3 due class canceled
14 Thr

3/16

MIDTERM EXAM RN 1-6; 17.6
01-09
--   material thru lecture 11 (3/8), 75 minute exam held in class
-- Tue 3/21 BREAK -- -- -- --
-- Thr 3/23 BREAK -- -- -- --
15 Tue 3/28 KR
RN 7
L13
Hunt the Wumpus; neats vs scruffies, Wason selection task; see notes 9.1.*
16 Thr 3/30 Propositional Logic RN 7 9.2

L14

  Wumpus 1980; Play Wumpus; Knowledge Base; see notes 9.2.*,
17 Tue 4/4 Prop. Logic Pro/Con; FOL
RN 8
L15    
18 Thr 4/6
FOL
RN 8
L16   family.pl, genesis.pl
19 Tue 4/11 Planning
RN 11.1-11.3
13.1
13.2
L17
HW4 out


STRIPS, Planning and scheduling, PDDL, planning.domains, planning repo

20 Thr 4/13 Bayes, BBNs
RN 12 13.1-2
L18   Bayes theorem video, Netica BBN Tutorial, Colab notebook
21 Tue 4/18 Machine learning, decision trees
RN19
L19

 

Google's Rules of Machine Learning, Unreasonable Effectiveness of Data
22 Thr 4/20 Decision trees, ML tools RN19
video
14.2
L20

HW4 due 4/21

Decision tree learning, weka, scikit-learn
23 Tue 4/25 ML tools

RN19

L21   Training, validation, test sets, Precision and recall, FI
24 Thr 4/27 Teaching in the Age of AI
4:30-6:00
--
zoom HWx out? recording coming soon
25 Tue 5/2 tools, methdology, SVM

RN19

L22 HW5 out Training, validation, test sets, Precision and recall, FI, Support vector machine
26 Thr 5/4 bagging, clustering
RN19
L23   clustering, ensemble learning, colab clustering notebooks, Bootstrap aggregating
27 Tue

5/9

clustering, neural networks
RN21
L24   colab notebooks, NN playground, backpropagation
28 Thr 5/11 neural networks RN21
14.nn.114.nn.2
14.nn.3
L25 HW5 due 5/14 colab notebooks, keras.io, word2vec demo
29 Tue 5/16 word embeddings, Transformers RN21 14.nn.4 L26   notebook, Huggingface transformers; OpenAI
-- Tue

5/23 3:30-5:30

FINAL EXAM
see
above
see
above
see
above

 

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