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.

ORDER This UFCFE3-15-1 Introductory Artificial Intelligence For Robotics Assignment NOW And Get Instant Discount