- 2012 Fall Semester
Undergraduate Course for Computer Science and Engineering
- Instructor:
Prof. Byoung-Tak
Zhang
- TA: Eun-Sol Kim (eskim ‘at’ bi.snu.ac.kr)
- Classroom:
Rm.
209, Bldg. 302 / Rm. 311-1, Bldg, 302
(Thu)
- Time: Tue &
Thu, 09:30-10:45
- Text:
o [1] The
Quest for Artificial Intelligence, Nilsson, N. J., Cambridge
University Press, 2009.
o [1] Cognitive
computing I: Multisensory perceptual intelligence in real-world (in
Korean), B.-T. Zhang, Mu-Song Yeu, Communications of KIISE,
30(1):75-87, 2012.
o [2] Cognitive
computing II: Machine vision-language learning in real-life (in Korean),
B.-T. Zhang, Dong-Hoon Lee, Communications of KIISE, 30(1):88-100,
2012.
o [3] Cognitive
computing III: Deep dynamic prediction in real-time (in Korean), B.-T.
Zhang, Hyun-Soo Kim, Communications of KIISE, 30(1):101-111, 2012.
o [4] Next-generation
machine learning technologies (in Korean), B.-T. Zhang, Communications of
KIISE, 25(3):96-107, 2007.
o Two open-book
exams (60%)
o Project
(30%)
o Reading and quiz
(5%)
o
Attendance and discussion (5%)
o To understand
the history of ideas and achievements in artificial intelligence (AI)
o To get
theoretical basis for developing computational models of AI
o To acquire the
conceptual and technical tools for application of artificial intelligence
o
To understand the future prospects of human-level
artificial intelligence
o MNIST_800 – 10 classes,
800 examples
o MNIST_2000 – 10
classes, 2000 examples
o CIFAR – only 2
classes
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Week
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Topics
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Slides
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Papers
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Questions
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1
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9/4
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Thinking
machines:
Leibniz, Frege, Turing, AI pioneers
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ch.1, ch.2, ch.3
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1_Turing
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Questions_1
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9/6
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Heuristic
programs:
logic, chess, checkers, 8-puzzle, GPS
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ch.3, ch.5, ch.14
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Questions_2
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2
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9/11
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Neural
networks and supervised learning algorithms
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NN, Ref
[4]
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9/13
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Practice
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3
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9/18
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Mobile
robots:
Shakey, FREDDY, tour guides, service robots
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ch.10, ch.12, ch.32
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Questions_3
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9/20
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New generation projects:
FGCS,
ESPRIT, SC
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ch.8, ch.16, ch.21
ch.22, ch.23
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Questions_4
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4
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9/25
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Bio-inspired
AI:
brain-style computing, simulating evolution
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ch.4, ch.24, ch.25, ch.35, Ref
[3]
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Questions_5
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9/27
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Practice - Perceptron
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Perceptron
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5
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No Class
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10/4
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Computer vision
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ch.9, ch.20, ch.30
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Questions_6
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6
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10/9
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Natural
language & speech:
Q&A, MT, NLP, HEARSAY-II
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ch.7, ch.13,
ch.17 ch.19, ch.30
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Questions_7
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10/11
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Practice - Weka & MLP
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Weka
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7
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10/16
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Review
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10/18
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Mid-term Exam
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8
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10/23
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Mid-term Presentation
(Due: Mid-term Report)
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10/25
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Expert
systems:
DENDRAL, MYCIN, PROSPECTOR, XCON
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ch.15, ch.18
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Questions_8
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9
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10/30
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Knowledge representation & reasoning:
semantic net, frames
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Symbolism and Connectionism
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ch.6, ch.11
ch.26,ch.27
Ref
[3]
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Questions_9
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11/1
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Practice – Weka & SVM
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Weka_SVM
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10
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11/6
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Machine
learning:
MBL, CBR, DT, NN, kNN, RL
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ch.29,
Ref
[4]
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Questions_10
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11/8
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Machine
learning:
MBL, CBR, DT, NN, kNN, RL
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ch.29,
Ref
[4]
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11
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11/13
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ML Practice
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11/15
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Cognitive
Robot Practice
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12
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11/20
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Probabilistic
graphical models (1):
LVM, BN, DBN
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ch.27, ch.28
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Questions_11
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11/22
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Intelligent
agents:
recommenders, assistants, IR, UI
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ch.31,ch.33,ch.34
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Questions_12
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13
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11/27
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Cognitive robots:
EU FP 6&7, humanoids, personal robots
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Human-leve AI:
Self-driving robot cars, Watson, Siri
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Ref
[1]
Ref
[2]
Ref
[3]
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11/29
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Cognitive
Robot Practice
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14
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12/6
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Final Exam
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15
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12/13(Changed!!!!!)
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Final Presentation (Poster)
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