CSE 591: Knowledge Representation and Reasoning (Spring 2012)
Time and Place TTh 3–4:15 p.m., BYAC 190
Instructor Joohyung Lee ([email protected])
Instructor’s Office Hours TTh 4:30–5:30 p.m., BY 472
Description Knowledge representation and reasoning (KRR) is one of the
fundamental areas in Artificial Intelligence. Any intelligent agent needs to
have adequate knowledge in order to behave intelligently. The KRR research
is concerned with how knowledge can be represented in formal languages and
manipulated in an automated way so that computers can make accurate
decisions derived from the knowledge base. Various methods have been
developed in the past 50 years, and it’s often discovered that they are in
fact closely related to each other. This is a graduate level course which
will introduce basic and recent developments in the research in knowledge
representation and reasoning.
Objectives Students who complete this course
• will understand the foundations of KRR and tradeoff between representation and reasoning
• will understand which knowledge-based techniques are appropriate for
which tasks;
• can use KRR systems and apply them to their research and real-world
problems;
• can write a research paper related to knowledge representation.
References These are references but not required. Relevant handouts will
be distributed.
• Handbook of knowledge representation. Edited by Frank van Harmelen, Vladimir Lifschitz, and Bruce Porter. Elsevier Science.
• Knowledge representation and reasoning. Ronald Brachman and Hector Levesque. Morgan Kaufmann Publishers.
1
Topics
1. Review of classical logic
2. Logic programming and answer set programming
3. Constraint processing
4. Temporal representation and reasoning
5. Ontology and the Semantic Web
6. Cognitive robotics
7. Knowledge representation for security
Grading The grade will be determined by class participation, two midterms,
homework and a project.
Class participation
Two midterms
Homework
Project
20%
30%
25%
25%
Class Participation For problems announced for class discussion, you are
expected to volunteer to present solutions to at least two problems at some
times during the semester; in this way you get credit for class participation.
This should be a solution that you found by yourself, without help from
others.
Homework Several times during the semester you will receive e-mail
messages with homework problems. When you work on these additional
problems, you may consult the materials handed out in class and your notes,
but not any books, and you should not accept any help.
Project The project is individual, or up to two people are allowed in a
team. You may choose your own topic, or the instructor will assist you in
selecting one. It is better to contact him early.
Initial proposal
Survey, progress report
Final report
10%
30%
60%
The syllabus is subject to change if necessary.
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CSE 591 Knowledge Representation and Reasoning (Spring 2012) ‑ Class Log
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1.5 Course introduction. Intro to KRR
Home
Class Log
Course Materials
Discussion board
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1.10 Continued intro to KRR. Intro to
NMCT and C+
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1.12
Multi­valued propositional
formulas
4
1.17
5
1.19
6
7
8
1.31
9
2.2
10
2.7
Language C+ (I)
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2.9
Language C+ (II)
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2.14
Expressive possibilities of
definite C+ (I)
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2.16
Expressive possibilities of
definite C+ (II)
14
2.21
Additive fluents
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2.23
Additive fluents continued
16
2.28
1st Test
17
3.1
History of nonmonotonic
reasoning
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3.6
Elaboration tolerance
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3.8
20
3.13
21
3.15
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Note­­­­­­­­­
­­­­
Classical Logic and
Knowledge Representation
NMCT (Sec 1 ­ 2.1)
Next
Problems :
1, 2
Semantics of causal theories
NMCT (Sec 2.2, 2.3)
Next
problems:
3
Equivalent transformation.
Constraints.
NMCT (Sec 2.4, 2.5)
Next
Problems:
4 ­ 9
1.24
Completion
NMCT Sec 3.1
1.26
MB in causal logic
NMCT Sec 3.2
Next
Problems:
Reasoning and planning
NMCT Sec 3.3
NP: 10, 11
Concurrent actions. Defeasible
rules
NMCT Sec 3.4, 3.5
NP: 12
edit navigation
krr‑s12.wikispaces.asu.edu/Class+Log
­­­­­­­­­­­Readings­­­­­­­­­­­
NP: 13, 14,
15
NP: 15, 16
Handout on Additive Fluents
Programs with Common Sense
Getting to the airport: the oldest planning problem
in AI
Elaboration Tolerance
mcp.pdf
A Knowledge Module: Buying and Selling
Representing the Zoo World and the Traffic World
in the language of the Causal Calculator
3.20
Spring break
3.22
Spring break
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3.27
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3.29
Review of FOL
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4.3
FOL problem solving
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4.5
Second­order logic,
circumscription, Robot with
Grippers
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4.10
Knowledge representation and classical
logic (pp. 1­16, excluding natural deduction)
circ.pdf
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CSE 591 Knowledge Representation and Reasoning (Spring 2012) ‑ Class Log
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4.10
27
4.12
Description Logic and OWL,
Protege
Scientific American_ Feature Article_ The
Semantic Web_ May 2001.pdf
A Practical Introduction to Ontologies and
OWL2.pdf
28
4.17
Description Logic and OWL
continued
Description logics (pp 1­10, 31­ 33)
29
4.19
Situation Calculus and Event
Calculus
Ch16.pdf scec.pdf intro to event calculus.pdf
4.24
Project Presentation
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