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CS165A: Artificial Intelligence: Syllabus |
Syllabus contents:
- General Information
- Prerequisites
- Course Objectives
- Class Attendance
- Textbook
- Computing Facilities
- Assignments and Grading
- Academic Integrity
- Students With Disabilities
Course
web site
Please check the course web site regularly for assigned
reading and homework, announcements, and any other relevant
information. Lecture notes will be posted to the web site prior to
each lecture, but these only contain a summary of the presented information. If you only read the lecture notes, you may
miss important information.
The
formal prerequisite is Computer Science 130A (Data Structures and Algorithms
I). This implies that you have studied topics such as algorithms, data
structures, searching and sorting techniques, recursion, and induction, all of
which are relevant to this course. Most importantly, you need to be able
to think logically about problems and solution strategies, and you must be
familiar enough with writing software to implement solutions on your own. If
you have completed the CS pre-major courses (including the Math and PSTAT
courses) and CS 130A then you will be very well-prepared.
What is this course about?
An introduction to the field of Artificial Intelligence
(AI), which attempts to understand and build intelligent systems. Topics include
intelligent agents, search, game playing, logic, knowledge representation and
reasoning, and uncertainty. We will also briefly cover the history of AI and
philosophical and social implications.
Overview
Artificial
Intelligence is about building and understanding intelligent systems. AI
means different things to different people. People have approached the
study of AI from various perspectives: philosophy, neurophysiology,
mathematics, linguistics, psychology, control systems, and computer science, to
name a few. Part of what makes it so interesting is the range of
activities, from trying to understand minds in the abstract, to building
creatures that run around and do things. AI has made steady progress and
contributed to much of what is now standard computer
science and cognitive science. It has spawned several sub-areas (e.g., natural
language processing, speech recognition, computer vision, robotics, expert
systems, and learning).
This
is a computer science course, so we are not primarily concerned with the
approaches of philosophy, cognitive science, etc., although we will come back
to them from time to time. We will cover the following topics:
History
and foundations of AI
Problem
solving and intelligent agents
Problem
solving and search (blind, informed, constraint satisfaction, adversarial)
Knowledge
representation and reasoning in deterministic environments (logic, semantic
networks, frames)
Knowledge
representation and reasoning in probabilistic environments (Bayesian networks)
Information retrieval and machine learning (classification and clustering)
Note
that CS165B, which sometimes is taught in the Spring quarter, is about machine learning. Hence we will only provide a
brief overview of
learning techniques in CS165A.
What you will learn
By
the end of the course, you will understand what AI is all about and what it has
contributed, and may contribute, to computing. You will have a working
knowledge of the basic tools of AI, which are applicable to a wide range of computing
problems. You will be able to solve problems using explicit knowledge and
reasoning. You will have experience building agents that, to some degree, can
perceive their environment, reason about their behavior, and act upon the
environment to achieve their goals.
This
is not primarily a programming course - that is, the main goal is to learn the
concepts, not to learn a language or particular programming techniques.
However, coding examples of the concepts is the best way to demonstrate (and facilitate)
your knowledge of them. Good programming practices (proper file structure,
comments, etc.) are expected.
Why study AI?
AI
techniques are used in building e-commerce (and other) agents, expert systems, speech
recognition and natural language processing software, intelligent user
interfaces, robotics, computer vision, and other areas of computing. A study of
the approaches and techniques of artificial intelligence can broaden your
perspective and give you a new set of tools to apply to a wide variety of
problems.
Class
attendance is required: you are responsible for everything that goes on in
class. Prepare in advance for class by reading and studying the assigned text,
and by making sure you understand the previous lecture.
Weekly
50-minute discussion sections, led by the TA, will focus on (1)
presenting supplementary material (such as practical examples) to the lectures, (2) answering questions (about lecture topics, homework problems,
programming issues, etc.), or by the instructor for make-up classes. It is required that students attend these sessions;
you are responsible for the material presented in these sessions. Students are
encouraged to give the TAs (and, if appropriate, the instructor) feedback
regarding topics or issues they would like to have discussed during this time.
Stuart
Russell and Peter Norvig, Artificial Intelligence:
A Modern Approach, Prentice Hall, Third Edition, 2010. (Otherwise known as AIMA.) This should be available in the UCSB
bookstore. A very thorough and useful web site for the text can be found
at http://aima.cs.berkeley.edu/. (Note
the errata that are listed at http://aima.cs.berkeley.edu/errata.html.)
You
may use the CSIL (Computer Science Instructional Lab) computers, or any other
machine you prefer. You should use either C/C++ or Java in your
assignments.
Grades will be based on homework assignments,
term project, weekly quizzes, midterm exam, and final exam:
20% Homework assignments
30% coding
assignment
20% Midterm exam
30% Final exam
Homework will include 4 assignments and 2 coding assignments.
Unless
otherwise instructed, all assignments must be handed in the class on the due
date.
After the due date, your score will be reduced 20% each day.
You
are encouraged to discuss homework assignments with classmates at a general
level. However, you may not share answers/code or collaborate on
solutions unless otherwise directed to do so. All work turned in must be
completely your own, including programming assignments. (See the Policy on
Academic Integrity, below.)
There
will be no makeup exams.
Please read this section carefully.
The
university, the department, and this instructor all take the issue of academic
integrity very seriously. A university requires an atmosphere of mutual
trust and respect. While collaboration is an integral part of many scholarly
activities, it is not always appropriate in a course, and it is never
appropriate unless due credit is given to all participants in the
collaboration. This goes for both ideas and programming or other work.
Here are some examples:
Allowed: Discussion of lecture and
textbook materials
Allowed: Discussion of how to approach
assignments, what techniques to consider, what textbook or lecture material is
relevant
Not allowed: Sharing ideas in the form
of code, pseudocode, or solutions
Not allowed: Turning in someone else's
work as your own, even with that person's permission.
Not allowed: Allowing someone else to
turn in your work as his or her own.
Not allowed: Turning in work without
proper acknowledgment of the sources of the content (including ideas) contained
within the work.
Summary:
Academic integrity is absolutely required - dishonesty (cheating, plagiarism,
etc.) benefits no one and hurts everyone. If you are not sure whether or
not something is appropriate, please ask the instructor or TA.
If
you are a student with a disability and would like to discuss special academic
accommodations, please contact the instructor. In addition, students with
temporary or permanent disabilities are referred to the Disabled Students Program (DSP) at
UCSB. DSP will arrange for special services when appropriate (e.g.,
facilitation of access, note takers, readers, sign
language interpreters). Please note that it is the student's
responsibility to communicate his or her special needs to the instructor, along
with a letter of verification from DSP.
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