Section 1: Overview of UFCFE3-15-1 Introductory Artificial Intelligence For Robotics Assignment
This assignment assesses the following module learning outcomes:
Design and implement intelligent solutions using at least two different architectures.
Design and implement a range of different search methods.
The assignment is worth 25% of the overall mark for the module.
The assignment is described in more detail in section 2.
This is an individual assignment.
Working on this assignment will help you to:
- Understand how a search-based framework can be used to solve different problems;
- Gain experience of the practical issues around creating machine learning systems;
- Demonstrate that you can implement a simple Machine Learning algorithm.
The code framework, supporting videos, and html documentation of the provided code-base will be provided in the “Assignments->Second Coursework” folder on Blackboard.
Section 2: Task Specification
In the lectures you will have been introduced to various paradigms for representing models.
In the tutorials you will have been introduced to an example C code framework for creating search-based solutions to problems.
The task is to use that framework to create a Machine Learning algorithm that can learn predictive Rule-Based models, using a greedy hill-climbing approach.
The system will present your code using a number of datasets. Each has 150 examples, split 100:50 between a ‘training set’ and ‘test’ set. Each example contains integer values for 6 features, and a single integer giving the class label between 0 and 5. Your code should:
- implement a train() function that ‘learn’ a set of rules from the training set. Some of the marks will be for implementing the right learning algorithm. For simplicity, your code should not generate solutions with more than 5 rules.
- implement a predictLabel() function that provide a predictions for a new case. Some of the marks will be for the effectiveness of your solution, i.e., its accuracy.
The code framework, supporting videos, and html documentation of the provided code- base will be provided in the “Assignments->Second Coursework” folder on Blackboard.
Section 3: Deliverables
The deliverable consists of a single file of C source code called Train And Test.c that implements at least two functions, one called train() and another called predictLabel().
- The exact syntax to be implemented will be supplied in the online documentation.
- The submitted files must make use of the supporting code-base, and produce results in the required format, otherwise they will lose marks.
- All submissions will be screened for security reasons – for example making “system()” calls or excessive memory use in C code will not be permitted.
- All code should be prepared using an platform-independent standard e.g. ANSI standard C rather than proprietary.