Overview

Artificial Intelligence is the area of computer science that concerns itself with "smart" solutions to problems. How can we find solutions faster than typical brute-force approaches by using knowledge about the problem? How can we use higher-orders of representation such as logic, graph structures, and others to solve problems? How can we learn from data or from the environment? How can we adapt the biological mechanisms of intelligence for computational purposes?

We'll consider all of the above as we examine a variety of problems in AI, including agent-based behavior (as in robotics), heuristic search, strategy game playing, supervised learning, reinforcement learning, logical deduction, and others.

Instructor Information

• Instructor: Dave Musicant
• Office: CMC 326
• Email: dmusican
• Office phone: (507)222-4369
• Office hours: See home page at http://www.cs.carleton.edu/faculty/dmusican

Graders:

• Tung Phan (email: phant)
• Bobby Davis (email: davisbo)

Textbook

• Artificial Intelligence: A Modern Approach, Stuart Russell & Peter Norvig, 3nd edition, Prentice-Hall, 2009.

Important Dates

• Exam 1: Friday, April 13
• Exam 2: Friday, May 4
• Exam 3: Friday, May 25
• Final project due: Monday, June 4

Your Grade

• Assignments: 40%
• Exam 1: 16%
• Exam 2: 16%
• Exam 2: 16%
• Class project: 12%

Assignments & Class Project

• The assignments will include both non-computer activities and programming.
• The class project is due at the end of the term. You can choose to do essentially anything inside the area of AI, so long as I approve it in advance. You can build on material we do in class, or you can use it as an opportunity to learn about subject matter we don't have time to cover.

Collaboration, Plagiarism, and the Difference Between the Two

There are two different kinds of working together: collaborating and plagiarism.

Collaborating

• Collaborating is good.
• You are encouraged to collaborate on ideas and program design.
• Programming is often a social effort, and there is much you can learn by talking out the ideas in this class with each other.
• You can by all means talk to each other, look at each others' programs to help fix problems, and share ideas.

Plagiarism

• Plagiarism is bad. DON'T DO IT!
• Any programs that you turn in should be your work.
• Even if you work with someone else and share ideas, you must still writ your own program.
• If a piece of your program utilizes someone else's idea, you must make sure to give that person credit in program comments.
• Do not hand a printout of your program to other students. I encourage you to work together to help debug your code, but you should do so sitting together.

• Taking someone else's program, changing comments and variable names, putting your name at the top, and turning it in.
• Finding a similar program on the Internet, changing the variables and comments around, putting your name at the top, and turning it in.
• Finding a similar program in a book, changing the variables and comments around, putting your name at the top, and turning it in.

I am compelled by Carleton policy to submit plagiarism cases that I find to the Dean of Students, who in turns brings the evidence before the Academic Standing Committee. The academic penalty for a finding of responsibility can range from a grade of zero in the specific assignment to a F in the course.

Working from your own computer

Most of the programming that we do will be in Python, which will be set up for use in the Computer Science labs. You should feel free to install Python on your home machine and work from there if you wish. If you do so, you are responsible for making sure that your programs work under the version of the compiler that we have installed in the labs. I am glad to informally provide whatever advice I can to help you get the software running on your own machine, but home use is technically "unsupported." We will be using Python 2, not Python 3.

Homework Policy

• Each assignment will have a specific time for which it will be due. An assignment turned in late within one day of the due time will be docked 25%. A program turned in later than one day of the due date but within two days will be docked 50%. An assignment turned in any time after this until the last day of classes will be docked 75%. If you turn in work late, it is your responsiblity to notify the grader(s) that you have done so, and that the assignment needs to be graded.
• College policy dictates that there can be no grace period on the final project.

Details

We will cover selected material potential from within the following chapters in Russell & Norvig:

• Chapter 1: Introduction
• Chapter 2: Intelligent Agents
• Chapter 3: Solving Problems by Searching
• Chapter 4: Beyond Classical Search
• Chapter 6: Adversarial Search
• Chapter 7: Logical Agents
• Chapter 8: First Order Logic
• Chapter 9: Inference in First-Order Logic
• Chapter 18: Learning from Examples
• Chapter 20: Learning Probabilistic Models
• Chapter 21: Reinforcement Learning
• Chapter 10: Classical Planning
• Chapter 11: Planning and Acting in the Real World
• Chapter 13: Quantifying Uncertainty
• Chapter 14: Probabilistic Reasoning
• Chapter 15: Probabilistic Reasoning over Time
• Chapter 16: Making Simple Decisions
• Chapter 25: Robotics
• Chapter 26: Philosophical Foundations