Why are you interested in this particular problem?

This assignment addresses all four Intended Learning Outcomes (ILOs) for this unit (see below). There are two parts to the submission (more on this below).

1. The source code (to solve a chosen problem) that you have implemented, to provide evidence of independent, technical, work (35% of total mark).

2. A technical report that covers the description of the problem, the methodology, and an empirical investigation (40% of total mark).

A key aspect of this assessment is demonstrating the ability to perform a critical analysis and evaluation. This involves empirical experiments, evaluating the performance of artificial intelligence algorithms and, potentially, data processing techniques, depending on the problem at hand.

You can choose to implement one of the algorithms we cover in the class or other algorithms as required by the targeted problem. In all cases, full details must be provided both in the documentation of the code and the report. The implementation must be in Python, Java or Matlab.

You are given the opportunity to choose yourself:

1) The project you are interested in any AI applications: natural language processing and understanding, machine vision, speech recognition, robotics, intelligent agents, smart environments, etc.

2) Your teammates (3 people max) - please give a name to your team.

You are asked to propose a project idea by following the traditional workflow:

- What is the problem to be solved?

- Why are you interested in this particular problem?

- Does the problem need datasets to be available? If so, which dataset is to be used?

- Which approach is appropriate for solving that problem? Please describe exactly the steps i.e. how you are going to deal with the problem at hand.

- Which algorithms are planned for the application?

- Which quality measures are to be used to evaluate the algorithms?

If you find it challenging to come up with your own project idea, you will need to discuss with the Unit Leader (UL) for advice and potential ideas. In all cases, should you need to discuss your project idea with UL, please make sure to submit a proposal (a brief description that covers the questions mentioned earlier), as soon as you have made your choice by arranging such a discussion preferably before 30/04/2020.

Please note that for your guidance, a sample of datasets will be made available on Brightspace (under the "Assessment" option). To learn about these datasets, please read the corresponding documentation (potentially the "Readme.txt" file once you have downloaded it). You can use these datasets or propose others, depending on the idea you are exploring in your project.

LO 1. Demonstrate an understanding of the principal challenges involved in AI, the major research areas, and the overall historical development of the field.