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Overview

This course introduces the design of intelligent agents, including the fundamental problem-solving and knowledge-representation paradigms of artificial intelligence. Topics to be covered include state-space and problem reduction methods, brute-force and heuristic search, two-player games, and recent developments in game AI. For knowledge representation and reasoning, we will cover propositional and first-order logic and their inference algorithms. Finally, the course covers probabilistic approaches to AI, such as Bayesian networks to improve the agent’s performance with experience.

Prerequisites

This course requires knowledge of basic computer science, algorithms and complexity (CS180), and programming principles.

Textbook

Stuart Russell and Peter Norvig. Artificial Intelligence: A Modern Approach. (3rd Edition), Pearson 2009.

Programming Language

Python

Logistics

  • Time: Tuesday and Thursday 2:00PM - 3:50PM

  • Location: Boelter 3400

  • Instructor: Quanquan Gu (Email: qgu at cs dot ucla dot edu)

  • Teaching Assistant:

    • [Xuheng Li] (Email: xuhengli99 at ucla dot edu)
    • [Jiafan He] (Email: jiafanhe19 at ucla dot edu)
    • [Weitong Zhang] (Email: weightzero at ucla dot edu)
    • [Yue Wu] (Email: wuy at ucla dot edu)

  • Discussion Sections:

    • Dis 1A - Xuheng Li - Boelter Hall 5280 - 10am - 11:50am
    • Dis 1B - Jiafan He - Boelter Hall 5419 - 12pm - 1:50pm
    • Dis 1C - Weitong Zhang - Franz Hall 1178 - 2pm - 3:50pm
    • Dis 1D - Yue Wu - Dodd Hall 170- 4pm - 5:50pm

  • Office hours:

    • The instructor's office hour is Wednesday 9:00am-10:00am in EVI 382.
    • The TA's office hour is:
      • Xuheng Li, Tuesday 12:00PM - 2:00PM, Boelter 3256S-D
      • Jiafan He, Monday 10:00 - 12:00PM boelter 3256S-D
      • Weitong Zhang, Thursday 4:00PM - 6:00PM, Boelter 3256S-A
      • Yue Wu, Wednesday 2:00 - 4:00PM, Boelter 3256S-D

  • Course Website: https://uclaml.github.io/CS161-Winter2023/

  • Course Forum: https://piazza.com/ucla/winter2023/cs161/home (If you haven’t already, sign up here.)

Grading Policy

Grades will be computed based on the following factors:

  • Homework 20%
  • Quiz 5%
  • Midterm 35%
  • Final 40%

Schedule

# Date Topics Reading Homework
1 1/10 About Course, Introduction: What is AI? Chapter 1,2
2 1/12 Problem solving as search & Uninformed search strategies Chapter 3
3 1/17 Uninformed search strategies Chapter 3 HW1 Out
4 1/19 Informed search strategies Chapter 3
5 1/24 Local Search Algorithms Chapter 4 HW1 Due, HW2 Out
6 1/26 Constraint satisfaction Chapter 6
7 1/31 Constraint satisfaction Chapter 6 HW2 Due, HW3 Out
8 2/2 Constraint satisfaction Chapter 6
9 2/7 Game playing Chapter 5
10 2/9 Game playing Chapter 5 Hw4 Out
11 2/14 Propositional logic Chapter 7 HW3 Due
2/16 Midterm Exam
12 2/21 Propositional logic Chapter 7 HW4 Due, HW5 Out
13 2/23 Propositional logic Chapter 7
14 2/28 First-order logic: representation Chapter 8
15 3/2 First-order logic: representation Chapter 8 HW5 Due, HW6 Out
16 3/7 First-order logic: inference Chapter 9
17 3/9 Reasoning under uncertainty Chapter 11
18 3/14 Bayesian Networks I Chapter 13
19 3/16 Bayesian Networks II Chapter 13 HW6 Due
3/22 3:00PM-6:00PM Final Exam

Academic Integrity Policy

Students are encouraged to read the UCLA Student Conduct Code for Academic Integrity.

Homework

There will be 6 homework assignments during the semester as we cover the corresponding material. Homework consists of both problem solving and programming. The lowest homework score will be dropped for you.

Unless otherwise indicated, you may talk to other students about the homework problems but each student must hand in their own answers and write their own code in the programming part. You also must indicate on each homework with whom you collaborated and cite any other sources you use including Internet websites. Students should never see another student's solution before submitting their own. Students cannot use old solution sets for this class or solution manual to the textbook under any circumstances.Homework assignments will be submitted through bruinlearn.

Please submit your homework on time. Homework is worth full credit before the due date. It is worth zero credit after the due date.

Quiz

There will be 6 in-class online quiz (on bruinlearn) for the purpose of reviewing the newly learned concepts. The quizzes are open textbook. We will drop the lowest quiz score for you.

Exams

There will be one midterm and then final. The exam is in person and open book and note. You are not allowed to discuss with other people.