Time: MW 11:00-12:20pm, Room
5313 (Sennott Square)
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| Lectures | Topic(s) | Assignments | |
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| August 29 |
Administrivia and course overview.
Readings: RN - chapters 1, 2. |
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| August 31 |
Problem solving by searching
Readings: RN - chapter 3, sections 3.1.-3.3. |
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| September 7 |
Uninformed search methods
Readings: RN - chapter 3, sections 3.4.-3.5. |
HW 1 assignment Programs HW1 Solution Solution programs |
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| September 12 |
Uninformed search methods
(finish). Informed search.
Readings: RN - chapter 3, sections 3.4.-3.5, and chapter 4. |
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| September 14 |
Informed search
Readings: RN - chapter 4 |
HW 2 Assignment Programs HW2 Solution Solution programs |
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| September 19 |
Constraint satisfaction search
Readings: RN - chapter 4 |
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| September 21 |
Search for the optimal configuration
Readings: RN - chapter 4.3, 4.4 |
HW 3 Assignment Programs HW3 Solution Solution programs |
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| September 26 |
Adversarial search
Readings: RN - chapter 6 |
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| September 26 |
Propositional logic
Readings: RN - chapter 7.1.-7.5. |
HW 4 Assignment Programs HW4 Solution Solution programs |
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| October 3 |
Propositional logic
Readings: RN - chapter 7. |
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| October 5 |
First order logic
Readings: RN - chapter 8 |
HW 5 Assignment Programs HW5 Solution Solution programs |
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| October 10 |
Inference in FOL
Readings: RN - chapter 8. |
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| October 12 |
Logic reasoning systems. Situation calculus.
Readings: RN - chapters 9, 10 |
HW 6 Assignment HW6 Solution |
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| October 17 |
Planning.
Readings: RN - chapter 11.1-11.3. |
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| October 19 |
Modeling uncertainty
Readings: RN - chapter 13. |
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| October 24 |
Midterm exam
Readings: Search, Knowledge representation, Planning |
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| October 26 |
Bayesian belief networks
Readings: RN - chapter 14. |
HW 7 Assignment HW 7 Solution |
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| October 31 |
Inference in Bayesian belief networks
Readings: RN - chapter 14. |
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| November 2 |
Inference in Bayesian belief networks
Readings: RN - chapter 14. |
HW 8 Assignment HW 8 Programs HW8 Solution Solution programs |
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| November 7 |
Decision making in the presence of uncertainty I
Readings: RN - chapter 16. |
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| November 9 |
Decision making in the presence of uncertainty II
Readings: RN - chapter 16. |
HW 9 Assignment HW 9 Solution |
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| November 14 |
Learning
Readings: RN - Chapter 18.1-18.3 |
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| November 16 |
Linear and logistic regression
Readings: Chapter 20.5. |
HW 10 Assignment Programs HW10 Solution Solution programs |
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| November 21 |
Multi-layer perceptron
Readings: Chapter 20.5. |
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| November 28 | No class | ||
| November 30 | Learning BBNs | HW 11 Assignment | |
| December 5 | Reinforcement learning | ||
| December 7 | Reinforcement learning (finish), Applied AI | ||
| December 12 | Course review | ||
| December 14 | Final Exam | ||
A collection of links to related material can be found here.
This course will provide an introduction to the fundamental concepts and techniques underlying the construction of intelligent computer systems. Topics covered in the course include: problem solving and search, logic and knowledge representation, planning, reasoning and decision-making in the presence of uncertainty, and machine learning.
Prerequisites: undergraduate level AI (CS 1571 or
equivalent) or the permission of the instructor
Textbook:
Stuart Russell,
Peter Norvig. Artificial Intelligence. A modern approach. 2ed. Prentice
Hall, 2002.
Note: The second edition of the book was published at the end of
2002. There are significant changes as compared to the first (1995) edition of the
book. Please make sure to obtain the new (green color cover) edition.
There will be weekly homework assignments. The homeworks will include a mix of paper and pencil problems, and programming assignments. The assignments are due at the beginning of the class on the day specified on the assignment. In general, no extensions will be granted.
Programming assignments. Knowledge of C/C++ language is neccessary for the programming part. C/C++ programs submitted by you should compile with g++ compiler under unix. Please see the rules for submitting programming assignments.
All the work in this course should be done independently. Collaborations on homeworks are not permitted. Cheating and any other antiintellectual behavior, including giving your work to someone else, will be dealt with severely. If you feel you may have violated the rules speak to us as soon as possible.
Please make sure you read, understand and abide by the Academic Integrity Code for the Faculty and College of Arts and Sciences.
Students With Disabilities
If you have a disability for which you are or may be requesting an accommodation, you are encouraged to contact both your instructor and Disability Resources and Services, 216 William Pitt Union, (412) 648-7890/(412) 383-7355 (TTY), as early as possible in the term. DRS will verify your disability and determine reasonable accomodations for this course.