CS3243
INTRODUCTION TO ARTIFICIAL INTELLIGENCE (2015/2016, Semester 2) 

 MODULE OUTLINE Created: 28-Dec-2015, Updated: 09-Jan-2016
 
Module Code CS3243
Module Title INTRODUCTION TO ARTIFICIAL INTELLIGENCE
Semester Semester 2, 2015/2016
Modular Credits 4
Faculty School of Computing
Department Computer Science
Timetable Timetable/Teaching Staff
Module Facilitators
DR Low Bryan Kian Hsiang Lecturer
NGUYEN QUOC PHONG Tutor
DMITRII KHARKOVSKII 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 1400-1600 LT19


 SYLLABUS Top

Week

Lecture Topics

Remarks

1     (11/01)

Introduction and Intelligent Agents

 

2     (18/01)

Intelligent Agents & Uninformed Search

 

3     (25/01)

Uninformed Search

 

4     (01/02)

Informed Search

 

5     (08/02)

Rescheduled from 8 Feb (Mon) to 10 Feb (Wed) 4-6pm in LT19 within same week: Adversarial Search​

 

6     (15/02)

NO CLASSES: Rescheduled to recess week 22 Feb (Mon) 2-4pm in LT19

 

RECESS WEEK (22/02)          Constraint Satisfaction

7     (29/02)

Logical Agents (Part 1)

 

8     (07/03)

MIDTERM EXAM

 

9     (14/03)

Logical Agents (Part 2)

 

10   (21/03)

First-Order Logic

 

11   (28/03)

Logical Inference

 

12   (04/04)

Uncertainty

 

13   (11/04)

Machine Learning

 

FINAL EXAM

Tuesday, 26 Apr 2016 (Evening)

 


 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