Module Details for Artificial Intelligence

Description

This module provides an introduction to some of the many Artificial Intelligence techniques which are currently, or could in the near future, be used to enhance the development of intelligent systems applied to various application domains.

Aims

The aim of this module is to provide the student with knowledge of how artificial intelligence techniques can be used effectively within an application environment to provide intelligence and/or the illusion of intelligence.

Learning Outcomes

By the end of this module the student should be able to:

1.  Critically examine various artificial intelligence techniques.

2.  Develop a critical understanding of AI techniques and technologies.

3.  Evaluate the use of AI technologies and techniques for specific purposes.

Indicative Content

1 ‘Traditional’ AI:

Rule Based Systems, Finite State Machines.

2 Academic AI Techniques:

Fuzzy Logic and Fuzzy State Machines, Case Based Reasoning, Genetic Algorithms, Reinforcement Learning, Probabilistic Techniques, Artificial Neural Networks, Clustering Algorithms.

3 Applications of AI:

Combining AI techniques to produce A-life and Intelligent Agents.

4 Machine Learning:

The ability of a machine to learn from its environment

5 Mining

Knowledge discovery and the process of finding hidden patterns in data

6 Big Data

The challenge of the 21st century is ‘too much data and not enough analysis’. Explore the challenges and opportunities afforded by this phenomenon.

7 Intelligence on the Internet:

Analyse the emergence of intelligent agents on the internet.

Teaching and Learning Work Loads