52 citations · 72 across the 12 of their papers we have counts for
14 papers
Denial of Wallet -- Defining a Looming Threat to Serverless Computing
Daniel Kelly, Frank G. Glavin, Enda Barrett
Serverless computing is the latest paradigm in cloud computing, offering a framework for the development of event driven, pay-as-you-go functions in a highly scalable environment.…
Serverless Computing: Behind the Scenes of Major Platforms
Daniel Kelly, Frank G Glavin, Enda Barrett
Serverless computing offers an event driven pay-as-you-go framework for application development. A key selling point is the concept of no back-end server management, allowing devel…
A Multi-class Approach -- Building a Visual Classifier based on Textual Descriptions using Zero-Shot Learning
Preeti Jagdish Sajjan, Frank G. Glavin
Machine Learning (ML) techniques for image classification routinely require many labelled images for training the model and while testing, we ought to use images belonging to the s…
Robust Classification of High-Dimensional Spectroscopy Data Using Deep Learning and Data Synthesis
James Houston, Frank G. Glavin, Michael G. Madden
This paper presents a new approach to classification of high dimensional spectroscopy data and demonstrates that it outperforms other current state-of-the art approaches. The speci…
A Virtual Testbed for Critical Incident Investigation with Autonomous Remote Aerial Vehicle Surveying, Artificial Intelligence, and Decision Support
David L. Smyth, Sai Abinesh, Nazli B. Karimi +4
Autonomous robotics and artificial intelligence techniques can be used to support human personnel in the event of critical incidents. These incidents can pose great danger to human…
Using a Game Engine to Simulate Critical Incidents and Data Collection by Autonomous Drones
David L. Smyth, Frank G. Glavin, Michael G. Madden
Using a game engine, we have developed a virtual environment which models important aspects of critical incident scenarios. We focused on modelling phenomena relating to the identi…
Skilled Experience Catalogue: A Skill-Balancing Mechanism for Non-Player Characters using Reinforcement Learning
Frank G. Glavin, Michael G. Madden
In this paper, we introduce a skill-balancing mechanism for adversarial non-player characters (NPCs), called Skilled Experience Catalogue (SEC). The objective of this mechanism is…
Adaptive Shooting for Bots in First Person Shooter Games Using Reinforcement Learning
Frank G. Glavin, Michael G. Madden
In current state-of-the-art commercial first person shooter games, computer controlled bots, also known as non player characters, can often be easily distinguishable from those con…
Analysis of the Effect of Unexpected Outliers in the Classification of Spectroscopy Data
Frank G. Glavin, Michael G. Madden
Multi-class classification algorithms are very widely used, but we argue that they are not always ideal from a theoretical perspective, because they assume all classes are characte…
Learning to Shoot in First Person Shooter Games by Stabilizing Actions and Clustering Rewards for Reinforcement Learning
Frank G. Glavin, Michael G. Madden
While reinforcement learning (RL) has been applied to turn-based board games for many years, more complex games involving decision-making in real-time are beginning to receive more…
DRE-Bot: A Hierarchical First Person Shooter Bot Using Multiple Sarsa(λ) Reinforcement Learners
Frank G. Glavin, Michael G. Madden
This paper describes an architecture for controlling non-player characters (NPC) in the First Person Shooter (FPS) game Unreal Tournament 2004. Specifically, the DRE-Bot architectu…
A One-Sided Classification Toolkit with Applications in the Analysis of Spectroscopy Data
Frank G. Glavin
This dissertation investigates the use of one-sided classification algorithms in the application of separating hazardous chlorinated solvents from other materials, based on their R…
A Virtual Environment with Multi-Robot Navigation, Analytics, and Decision Support for Critical Incident Investigation
David L. Smyth, James Fennell, Sai Abinesh +5
Accidents and attacks that involve chemical, biological, radiological/nuclear or explosive (CBRNE) substances are rare, but can be of high consequence. Since the investigation of s…
Colwell's Castle Defence: A Custom Game Using Dynamic Difficulty Adjustment to Increase Player Enjoyment
Anthony M. Colwell, Frank G. Glavin
Dynamic Difficulty Adjustment (DDA) is a mechanism used in video games that automatically tailors the individual gaming experience to match an appropriate difficulty setting. This…