Introduction to Artificial Intelligence, 2017 Spring

Quicklinks

Course overview
Schedule
Prerequisites
Objectives
Homeworks, exams, and grading

Course overview

Final exam: Friday 12/22 11:30-2:30
Time and place: Mondays and Thursdays, 2:00-3:50 pm, DARRIN 318
- Lab Sec 1: Wed 6:00-7:50 pm, Eaton 216. TA: Evan (strohe@rpi.edu). Mentors: Louis (hydel@rpi.edu), Haoming (lih14@rpi.edu).
- Lab Sec 2: Wed 2:00-3:50 pm, LOW 3039. TA: Haidar (khanh2@rpi.edu). Mentors: Alex (seoa@rpi.edu), Haoming (lih14@rpi.edu)
- Lab Sec 3: Wed 2:00-3:50 pm, SAGE 2715. TA: Yuchen (liangy7@rpi.edu). Mentors: Peter (woodp@rpi.edu), Yunhe (wangy43@rpi.edu)
- Lab Sec 4: Wed 12:00-1:50 pm, SAGE 2715. TA: Yuchen (liangy7@rpi.edu). Mentors: Yunhe (wangy43@rpi.edu), Mengyi (lim18@rpi.edu)
- Lab Sec 5: Wed 10:00-11:50 am, SAGE 3713. TA: Haidar (khanh2@rpi.edu). Mentors: Gregory (hanseg3@rpi.edu), Mengyi (lim18@rpi.edu)
- Lab Sec 6: Wed 12:00-1:50 pm, SAGE 3704. TA: Evan (strohe@rpi.edu). Mentors: Alex (seoa@rpi.edu), Gregory (hanseg3@rpi.edu)
Instructor: Lirong Xia (xial@cs.rpi.edu). Please call me Lirong.
TAs
- Yuchen Liang (liangy7@rpi.edu). Sec 3 & 4
- Evan Strohmg (strohe@rpi.edu). Sec 1 & 6
- Haidar Khan (khanh2@rpi.edu). Sec 2 & 5
UG mentors
- Hyde, Louis (hydel@rpi.edu). Piazza, Sec 1
- Seo, Alex (seoa@rpi.edu). Sec 2 & 6
- Wood, Peter (woodp@rpi.edu). Piazza, Sec 3
- Li, Haoming (lih14@rpi.edu). Sec 1 & 2
- Hansell, Gregory (hanseg3@rpi.edu). Sec 5 & 6
- Wang, Yunhe (wangy43@rpi.edu). Sec 3 & 4
- Li, Mengyi (lim18@rpi.edu). Sec 4 & 5
Office hours:
- Use Piazza first! You will get more timely help and everyone will benefit from your questions.
- Lirong Xia: Fridays 1-3 pm or by appointment, Lally 306

Announcements

11-20. HW7 is out.

11-16. HW6 is out.

10-30. HW5 is out.

10-26. Lab 4 is out.

10-18. HW4 is out.

10-12. Lab 3 is out.

10-3. HW3 out, due on 10-12. Recommend working on it before the exam as a practice.

9-21. HW2 out, due on 9-28

9-8. Lab 2 is out.

9-8. Homework 1 is out, due Sep 14 before the class.

Schedule (Subject to change)

Week	Date	Topic	Assignments	Wed labs
1
1	8-31	Introduction to Algorithms: Chap 0	Read the syllabus carefully Sign up on Piazza Vote on OPRA for office hours Join CSCI 2300 OPRA Group
2	9-4	Labor Day, no class		9-6 Lab 1
2	9-7	Introduction to Algorithms: Chap 0		9-6 Lab 1
3	9-11	Graph Algorithms: Sections 3.1, 4.1-4.2		9-13 Recitation/ Office hours
3	9-14	Graph Algorithms: Sections 3.1, 4.1-4.2	HW1 due	9-13 Recitation/ Office hours
4	9-18	Graph Algorithms: Sections 3.2-3.4		9-20 Lab 2
4	9-21	Graph Algorithms: Sections 3.2-3.4		9-20 Lab 2
5	9-25	Graph Algorithms: Sections 4.3-4.5, 4.7		9-27 Recitation/ Office hours
5	9-28	Greedy Algorithms: Section 5.1	HW2 due	9-27 Recitation/ Office hours
6	10-2	Greedy Algorithms: Interval Scheduling		10-4 Recitation/ Office hours
6	10-5	Greedy Algorithms: Interval Scheduling		10-4 Recitation/ Office hours
7	10-10 TUES, following Monday schedule	In-class Exam 1		10-11 Recitation/ Office hours
7	10-12	Divide and Conquer: Section 2.3	HW3 due	10-11 Recitation/ Office hours
8	10-16	Divide and Conquer: Sections 2.1-2.2		10-18 Lab 3
8	10-19	Divide and Conquer, Randomized Algorithms:Sections 2.4-2.5		10-18 Lab 3
9	10-23	Divide and Conquer, Randomized Algorithms:Sections 2.4-2.5		10-25 Recitation/ Office hours
9	10-26	Dynamic Programming: Sections 6.1-6.3	HW4 due	10-25 Recitation/ Office hours
10	10-30	Dynamic Programming: Sections 6.1-6.3		11-1 Lab 4
10	11-2	Dynamic Programming: Sections 6.4, 6.7		11-1 Lab 4
11	11-6	Dynamic Programming: Sections 6.4, 6.7		11-8 Recitation/ Office hours
11	11-9	Dynamic Programming: Sections 4.6, 6.6	HW5 due	11-8 Recitation/ Office hours
12	11-13	Network Flow and Linear Programming: Sections 7.1-7.2		11-15 Recitation/ Office hours
12	11-16	In-class Exam 2		11-15 Recitation/ Office hours
13	11-20	Network Flow and Linear Programming: Sections 7.2-7.3		None
13	11-23	Thanksgiving holiday		None
14	11-27	NP-Complete Problems: Chapter 8		11-29 Recitation/ Office hours
14	11-30	NP-Complete Problems: Chapter 8	HW6 due	11-29 Recitation/ Office hours
15	12-4	NP-Complete Problems: Chapter 8		12-6 Recitation/ Office hours
15	12-7	NP-Complete Problems: Chapter 8	HW7 due	12-6 Recitation/ Office hours
16
16

Final exam: Friday 12/22 11:30-2:30

DCC 318: if your RIN is an even number (ending with 0, 2, 4, 6, 8)

DCC 324: if your RIN is an odd number (ending with 1, 3, 5, 7, 9)

Textbook

Algorithms by Dasgupta, Papadimitriou, and Vazirani. See also the textbook errata.

Prerequisites

A qualified student must have taken the following courses or their equivalents
1. CSCI 1200
2. CSCI 2200

Objectives

This course presents fundamental ideas and techniques of modern algorithm design and analysis. After completing this course, students should be able to analyze and design efficient algorithms for a variety of computational problems. Students will learn a variety of algorithm design techniques, how to apply them to different problems, and how to choose which technique should be used for which problem. For more details, see the Syllabus.

The pre-requisites for this course are CSCI 1200 and 2200. We will assume that everyone has seen the material in these courses, and will use it as necessary.

Homeworks, exams, and grading

Students are highly encouraged to attend all classes. You are responsible for all material covered and announcements made in lecture.

Homework. Homework will be assigned every 1-2 weeks. Homework should be handed in at the beginning of lecture in class on the day it is due. For homework policies, see the 2300 Homework Guide.

Labs and Recitations. Labs will take place every Wednesday, and your attendance is required. For details and lab policies, see the 2300 Lab Guide.

Exams. There will be two midterm exams in class on October 10 and November 16, and a comprehensive final exam during finals week. All exams are open-textbook and open-notes. Make-up exams will not be given except in case of an emergency, accompanied by a letter from the Dean of Students excusing your absence from the exam. Students who know they are going to miss an exam must notify us in advance. Special circumstances can be accommodated if we are notified about them in advance.