CS3243
INTRODUCTION TO ARTIFICIAL INTELLIGENCE (2014/2015, Semester 2) 

 MODULE OUTLINE Created: 09-Jan-2015, Updated: 09-Jan-2015
 
Module Code CS3243
Module Title INTRODUCTION TO ARTIFICIAL INTELLIGENCE
Semester Semester 2, 2014/2015
Modular Credits 4
Faculty School of Computing
Department Computer Science
Timetable Timetable/Teaching Staff
Module Facilitators
DR Low Bryan Kian Hsiang Lecturer
Consultation : Send me an email at lowkh@comp.nus.edu.sg for an appointment.
ZHANG YEHONG Tutor
SON JAEMIN Tutor
Weblinks
Tags --


Learning Outcomes | Prerequisites | Schedule | Syllabus | Assessment | Preclusions | Workload


 LEARNING OUTCOMES Top
The module introduces the basic concepts in search and knowledge representation as well as to a number of sub-areas of artificial intelligence. It focuses on covering the essential concepts in AI. The module covers intelligent agents; uninformed/blind search: breadth-first search, uniform-cost search, depth-first search, depth-limited search, iterative deepening search; informed/heuristic search: greedy best-first search, A* algorithm; local search: hill climbing and simulated annealing; adversarial search: minimax algorithm and alpha-beta pruning; constraint satisfaction problems: backtracking search, constraint propagation, local search; logical agents: propositional logic, first-order logic, logical inference; uncertainty: Bayes’ rule, Bayesian inference, independence and conditional independence, Bayesian networks; machine learning: decision tree learning, naive Bayes classifier.


 PREREQUISITES Top
(CS2010 or its equivalent) and (CS1231 or MA1100).


 SCHEDULE Top
Lectures: Mon 1200-1400 I3 Auditorium


 SYLLABUS Top

Week

Lecture Topics

Remarks

1     (12/01)

Introduction and Intelligent Agents

 

2     (19/01)

Uninformed Search

 

3     (26/01)

NO CLASSES: Rescheduled to recess week 23 Feb (Mon) 12-2pm in I3 Auditorium

 

4     (05/02)

Rescheduled from 2 Feb (Mon) to 5 Feb (Thurs) 12-2pm in I3 Auditorium within same week: Informed Search 

 

5     (09/02)

Adversarial Search

 

6     (16/02)

Constraint Satisfaction

 

RECESS WEEK (23/02)          Logical Agents (Part 1)

7     (02/03)

Logical Agents (Part 2)

 

8     (09/03)

MIDTERM EXAM

 

9     (16/03)

First-Order Logic

 

10   (23/03)

Logical Inference

 

11   (30/04)

Uncertainty

 

12   (06/04)

Machine Learning

 

13   (13/04)

Exam Revision

 

FINAL EXAM

Wednesday, 29 Apr 2015 (Afternoon)

 



 ASSESSMENT Top
Class participation + Homework Assignments + Term Project 30%
Midterm Exam 20%
Final Exam 50%
 



 PRECLUSIONS Top
EEE and CPE students can only take this module as a technical elective to satisfy the program requirements or UEM but not CFM/ULR-Breadth.


 WORKLOAD Top
2-1-0-3-4

Workload Components : A-B-C-D-E
A: no. of lecture hours per week
B: no. of tutorial hours per week
C: no. of lab hours per week
D: no. of hours for projects, assignments, fieldwork etc per week
E: no. of hours for preparatory work by a student per week