Module ICP-1025:
Intro to Intelligent Systems

Module Facts

Run by School of Computer Science and Electronic Engineering

10 Credits or 5 ECTS Credits

Semester 2

Organiser: Dr William Teahan

Overall aims and purpose

Aims: 1. To introduce Artificial Intelligence (AI) and intelligent systems – AI concepts, tools and technologies used in building intelligent systems. 2. To review AI applications and likely future directions. 3. To provide an introduction to the field of intelligent agents, knowledge representation and knowledge engineering. 4. To compare and contrast agent-oriented systems with object oriented systems and introduce agent-oriented programming, agent-directed simulation and modelling.

Course content

Introduction to Artificial Intelligence and AI technologies used in computing systems.

AI application areas and likely future directions.

AI on the Internet: e.g. World Wide Web spiders (“bots”) and search engines.

AI used in games and movie-making (e.g. the MASSIVE system used in movies such as Avatar, the Hobbit, King Kong.)

Introduction to the fields of Intelligent Agents, Knowledge Representation and Knowledge Engineering: Propositional logic; first order logic; rule-based systems; semantic networks; frames.

Agent oriented programming versus object oriented programming. Introduction to agent-oriented programming and agent directed simulation and modelling (e.g. in NetLogo).

Learning outcomes mapped to assessment criteria

  threshold

(40% - 60%) Has a basic knowledge of most of the course material and can analyse and design familiar systems.

good

(60% - 70%) Understands most of the course material and can analyse and design most unfamiliar systems.

excellent

(70% or above) Understands most of the course material and can analyse and design most unfamiliar systems.

At the end of this module the student should demonstrate knowledge and understanding of the following (to a level indicated by exam, laboratory and assignment questions): 1. AI systems: AI concepts, agent tools and technologies used in computing systems.

Understands most of the course material and can analyse and design most unfamiliar systems. Has a basic knowledge of most of the course material and can analyse and design familiar systems. Has a good understanding of the course material and an ability to analyse and design non-trivial programs to a good standard.

At the end of this module the student should demonstrate knowledge and understanding of the following (to a level indicated by exam, laboratory and assignment questions): 3. Intelligent agents; Knowledge Representation; Knowledge Engineering.

Has a good understanding of the course material and an ability to analyse and design non-trivial programs to a good standard. Has a basic knowledge of most of the course material and can analyse and design familiar systems. Understands most of the course material and can analyse and design most unfamiliar systems.

At the end of this module the student should demonstrate knowledge and understanding of the following (to a level indicated by exam, laboratory and assignment questions): 4. AI-based systems on the Internet; e.g.World Wide Web spiders (“bots”) and search engines.

Understands most of the course material and can analyse and design most unfamiliar systems. Has a basic knowledge of most of the course material and can analyse and design familiar systems. Has a good understanding of the course material and an ability to analyse and design non-trivial programs to a good standard.

At the end of this module the student should demonstrate knowledge and understanding of the following (to a level indicated by exam, laboratory and assignment questions): 5. AI used in games and movie-making.

Understands most of the course material and can analyse and design most unfamiliar systems. Has a basic knowledge of most of the course material and can analyse and design familiar systems. Has a good understanding of the course material and an ability to analyse and design non-trivial programs to a good standard.

At the end of this module the student should demonstrate knowledge and understanding of the following (to a level indicated by exam, laboratory and assignment questions): 2. AI application areas and likely future directions.

Has a basic knowledge of most of the course material and can analyse and design familiar systems. Has a good understanding of the course material and an ability to analyse and design non-trivial programs to a good standard. Understands most of the course material and can analyse and design most unfamiliar systems.

At the end of this module the student should demonstrate knowledge and understanding of the following (to a level indicated by exam, laboratory and assignment questions): 6. Agent-oriented systems versus object oriented systems; agent direction simulation and modelling (e.g. in NetLogo).

Has a good understanding of the course material and an ability to analyse and design non-trivial programs to a good standard. Has a basic knowledge of most of the course material and can analyse and design familiar systems. Understands most of the course material and can analyse and design most unfamiliar systems.

Assessment Methods

Type Name Description Weight
Laboratory exercises 80
Open Book Test 20

Teaching and Learning Strategy

Hours
Lecture

24 hours over 12 weeks

24
Individual Project

Individual assignment worth 25%.

25
Laboratory

Lab sessions scheduled 1 hour per week; hours include lab preparation and writing of report.

15
Private study

Private study: revision for exam etc.

36

Transferable skills

  • Literacy - Proficiency in reading and writing through a variety of media
  • Numeracy - Proficiency in using numbers at appropriate levels of accuracy
  • Computer Literacy - Proficiency in using a varied range of computer software
  • Self-Management - Able to work unsupervised in an efficient, punctual and structured manner. To examine the outcomes of tasks and events, and judge levels of quality and importance
  • Exploring - Able to investigate, research and consider alternatives
  • Information retrieval - Able to access different and multiple sources of information
  • Critical analysis & Problem Solving - Able to deconstruct and analyse problems or complex situations. To find solutions to problems through analyses and exploration of all possibilities using appropriate methods, rescources and creativity.
  • Argument - Able to put forward, debate and justify an opinion or a course of action, with an individual or in a wider group setting

Subject specific skills

  • Identify emerging technologies and technology trends;
  • Apply underpinning concepts and ideas of engineering;
  • Apply knowledge and understanding of the specialist cognate area of computer systems engineering in an international context;
  • Apply knowledge and understanding of the specialist cognate area of computer systems for controlling complex systems;
  • Solve problems logically and systematically;
  • Assess and choose optimal methods and approaches for the specification, design, implementation and evaluation of engineering solutions.
  • Demonstrate familiarity with relevant subject specific and general computer software packages.
  • Knowledge and understanding of facts, concepts, principles & theories
  • Use of such knowledge in modelling and design
  • Problem solving strategies
  • Analyse if/how a system meets current and future requirements
  • Deploy theory in design, implementation and evaluation of systems
  • Recognise legal, social, ethical & professional issues
  • Specify, design or construct computer-based systems
  • Evaluate systems in terms of quality and trade-offs
  • Deploy tools effectively
  • Specify, deploy, verify and maintain information systems
  • Defining problems, managing design process and evaluating outcomes
  • System Design
  • Knowledge and/or understanding of appropriate scientific and engineering principles
  • Knowledge and understanding of mathematical principles
  • Knowledge and understanding of computational modelling
  • Principles of appropriate supporting engineering and scientific disciplines

Pre- and Co-requisite Modules

Courses including this module