Project Abstract

Motivation of this work will be to combine AI methods of reasoning with Machine Learning algorithms. I chosen to do this project due to the emergence of AI in recent times, which has seen a great impact along the world. Machine Learning is also something I have enjoyed using in my university studies.The main aim is to explore which methods of AI Reasoning and Machine Learning I can combine to ensure the best results of my work. I will be exploring rule-based reasoning and XAI models and trying to combine them together to explain factors like feature importance and making predictions based on sample cases in my program.The approach to my program relates to buses in the city of Swansea. I use rule-based reasoning to check for ticket eligibility based on a number of conditions related to ticket type that is purchased, and then also use machine learning to make predictions on whether the bus will be early, on time, or late depending on numerous factors (such as weather, delays, traffic etc). The insights look to showcase how using the combination of AI Reasoning and Machine Learning, we can be able to showcase results more clearly and in a more interesting way. There is of course improvements that can be made, espeically since I have limited experience using XAI models, as well as other approaches to this experiement which I could have considered in the future.

Keywords: Machine Learning, Artificial Intelligence, Explainable AI Models

 Conference Details

Session: Poster Session A at Poster Stand 95

Location: Sir Stanley Clarke Auditorium at Tuesday 7th 13:30 – 17:00

Markers: Bertie Muller, Hoang Nga Nguyen

Course: BSc Computer Science, 3rd Year

Future Plans: I’m undecided