CE213-5-AU-CO:
Introduction to Artificial Intelligence
PLEASE NOTE: This module is inactive. Visit the Module Directory to view modules and variants offered during the current academic year.
2023/24
Computer Science and Electronic Engineering (School of)
Colchester Campus
Autumn
Undergraduate: Level 5
Inactive
Thursday 05 October 2023
Friday 15 December 2023
15
21 July 2023
Requisites for this module
(none)
(none)
(none)
(none)
CE345
This module provides an introduction to three fundamental areas of artificial intelligence: search, knowledge representation and learning. These underpin all more advanced areas of artificial intelligence and are of central importance to related fields such as computer games and robotics.
Within each area, a range of methodologies and techniques are presented; emphasis is placed on understanding their strengths and weaknesses and hence on assessing which is most suited to a particular task. The module also provides an introduction to the philosophical arguments about the possibility of a machine being able to think. It concludes with a brief overview of systems based on interacting intelligent agents.
This module aims to provide an introduction to three fundamental areas of artificial intelligence: search, knowledge representation and learning.
After completing this module, students will be expected to be able to:
1. Explain and criticise the arguments that have been advanced both for and against the possibility of artificial intelligence.
2. Explain and implement standard blind and heuristic search procedures, demonstrate an understanding of their strengths and weaknesses and of how they may be applied to solve well-defined problems.
3. Explain the operation of standard production system interpreters, and demonstrate an understanding of their relative merits.
4. Explain the operation of a range of established machine learning procedures and demonstrate an understanding of the types of problems for which they are appropriate.
5. Demonstrate an understanding of the agent-oriented approach to artificial intelligence, and explain how a multi-agent system of purely reactive agents may be built using a subsumption architecture.
Outline Syllabus
1. Introduction
What AI is and is not
The debate about whether AI is possible
2. Solving problems by searching
State space representation
Search trees and graphs
Blind search strategies - depth first, breadth first and iterative deepening
Heuristic search - greedy search and A* search
Hill climbing
Game playing - minimax search
Means ends analysis
Implementing search
3. Using knowledge to solve problems
The importance of domain knowledge
Rule based systems
Forward chaining rule interpreters
Backward chaining rule interpreters
4. Acquiring knowledge - machine learning
Decision tree induction
Neural networks - back propagation
Clustering - k means algorithm
Reinforcement learning - Q algorithm
Genetic algorithms
5. Intelligent agents
Reactive v. deliberative agents
Subsumption architectures for purely reactive agents
The above list is indicative of the essential reading for the course.
The library makes provision for all reading list items, with digital provision where possible, and these resources are shared between students.
Further reading can be obtained from this module's
reading list.
Assessment items, weightings and deadlines
| Coursework / exam |
Description |
Deadline |
Coursework weighting |
| Exam |
Main exam: In-Person, Open Book (Restricted), 120 minutes during Summer (Main Period)
|
| Exam |
Reassessment Main exam: In-Person, Open Book (Restricted), 120 minutes during September (Reassessment Period)
|
Exam format definitions
- Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
- In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
- In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
- In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary,
for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.
Your department will provide further guidance before your exams.
Overall assessment
Reassessment
Module supervisor and teaching staff
CSEE School Office, email: csee-schooloffice non-Essex users should add @essex.ac.uk to create full e-mail address), Telephone 01206 872770
Yes
No
Yes
Prof Pietro Oliveto
Southern University of Science and Technology (SUSTech)
Professor
Available via Moodle
Of 41 hours, 38 (92.7%) hours available to students:
3 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).
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