Module Code - Title:
CS4006
-
INTELLIGENT SYSTEMS
Year Last Offered:
2025/6
Hours Per Week:
Grading Type:
N
Prerequisite Modules:
Rationale and Purpose of the Module:
The purpose of this module is to familiarise students with a targeted subset of the principles and methods of Intelligent Systems, together with an overall perspective on the field as a whole.
Syllabus:
To provide students with an understanding of the basic principles, methods and application domains for Intelligent Systems and Artificial Intelligence. To introduce students to the core issues involved in the development of Intelligent Systems. This module introduces the history and development of Intelligent system concepts. It includes discussions on uninformed and informed (heuristic) search, Expert Systems and bio-inspired intelligence, and looks at issues arising in problem representation, automated reasoning, and machine learning, together with the introduction of a set of design principles for intelligent autonomous agents. This module also looks to the possible future potential of such agents (both disembodied and embodied) and introduces the idea of Artificial General Intelligence.
Real world applications of the course topics are also presented in areas such as robotics and financial prediction.
Learning Outcomes:
Cognitive (Knowledge, Understanding, Application, Analysis, Evaluation, Synthesis)
On successful completion of this module, students will be able to:
1. Describe the phylogenetic, ontogenetic, epigenetic (POE) model of bio-inspired intelligent systems and show how the POE axes can be combined to create novel intelligent systems.
2. Explain and describe the principles of heuristic search and apply these techniques to representational examples.
3. Given a set of facts and a number of associated rules, apply a production inference mechanism to establish the identity of the facts.
4.Outline the principal forms of machine learning and be familiar with the application of a supervised learning method to small-scale problems.
Affective (Attitudes and Values)
N/A
Psychomotor (Physical Skills)
N/A
How the Module will be Taught and what will be the Learning Experiences of the Students:
This module is taught via a combination of lecture and/or tutorial sessions where the students are introduced to some of the core areas in the Intelligent Systems field. Recent developments and research findings will be presented in the form of up-to-date significant research papers in the field. In addition, students will complete substantial project work as part of the module demonstrating their knowledge and competence in core areas of the field. These will be group projects, thus contributing to the collaborative, knowledgeable and creative graduate attributes of the students.
Research Findings Incorporated in to the Syllabus (If Relevant):
Prime Texts:
G. Luger (2009)
Artificial Intelligence (6th edition)
, Addison-Wesley
Stuart J. Russell and Peter Norvig (2020)
Artificial Intelligence: A Modern Approach (4th edition)
, Prentice Hall
Other Relevant Texts:
R. J. Schalkoff (2011)
Intelligent systems: Principles, paradigms and pragmatics.
, Jones & Bartlett Publishers.
J. Copeland (1993)
Artificial Intelligence: A Philosophical Introduction
, Blackwell Publishers
Programme(s) in which this Module is Offered:
Semester(s) Module is Offered:
Spring
Module Leader:
dhiraj.kumarsingh@ul.ie