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Module Overview


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CS3243 

INTRODUCTION TO ARTIFICIAL INTELLIGENCE
   2014/2015, Semester 2
   School of Computing (Computer Science)
Modular Credits: 4
  Tags: --

Learning Outcomes

TopThe 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

TopLectures: 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

TopEEE 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

Top2-1-0-3-4

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

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