Avoidance Strategies in Particle Swarm Optimisation. - Karl Mason; Enda Howley (MENDEL, 2015)

Multi-Objective Dynamic Dispatch Optimisation using Multi-Agent Reinforcement Learning: (Extended Abstract). - Patrick Mannion; Karl Mason; Sam Devlin; Jim Duggan; Enda Howley (AAMAS, 2016)

Neural network topology and weight optimization through neuro differential evolution. - Karl Mason; Jim Duggan; Enda Howley (GECCO (Companion), 2017)

Evolving multi-objective neural networks using differential evolution for dynamic economic emission dispatch. - Karl Mason; Jim Duggan; Enda Howley (GECCO (Companion), 2017)

Predicting host CPU utilization in cloud computing using recurrent neural networks. - Martin Duggan; Karl Mason; Jim Duggan; Enda Howley; Enda Barrett (ICITST, 2017)

Policy invariance under reward transformations for multi-objective reinforcement learning. - Patrick Mannion; Sam Devlin; Karl Mason; Jim Duggan; Enda Howley (Neurocomputing, 2017)

Multi-objective dynamic economic emission dispatch using particle swarm optimisation variants. - Karl Mason; Jim Duggan; Enda Howley (Neurocomputing, 2017)

A meta optimisation analysis of particle swarm optimisation velocity update equations for watershed management learning. - Karl Mason; Jim Duggan; Enda Howley (Appl. Soft Comput., 2018)

Predicting host CPU utilization in the cloud using evolutionary neural networks. - Karl Mason; Martin Duggan; Enda Barrett; Jim Duggan; Enda Howley (Future Gener. Comput. Syst., 2018)

An "On The Fly" Framework for Efficiently Generating Synthetic Big Data Sets. - Karl Mason; Sadegh Vejdan; Santiago Grijalva (IEEE BigData, 2019)

A review of reinforcement learning for autonomous building energy management. - Karl Mason; Santiago Grijalva (Comput. Electr. Eng., 2019)

Building HVAC Control via Neural Networks and Natural Evolution Strategies. - Karl Mason; Santiago Grijalva (CEC, 2021)

Know Your Enemy: Identifying Adversarial Behaviours in Deep Reinforcement Learning Agents (Student Abstract). - Seán Caulfield Curley; Karl Mason; Patrick Mannion (AAAI, 2023)

Integrating Artificial Intelligence into Electric Vehicle Energy Systems: A Survey. - Weiqi Hua; Daniel Mullen; Abdul Wahid; Khadija Sitabkhan; Karl Mason (AI4KMES@ECAI, 2023)

Know Your Enemy: Identifying and Adapting to Adversarial Attacks in Deep Reinforcement Learning. - Seán Caulfield Curley; Karl Mason; Patrick Mannion (AAMAS, 2023)

Reinforcement Learning for Battery Management in Dairy Farming. - Nawazish Ali; Abdul Wahid; Rachael Shaw; Karl Mason (ECAI Workshops (2), 2023)

An Overview of Artificial Intelligence for Electric Vehicle Energy Systems Integration. - Weiqi Hua; Daniel Mullen; Abdul Wahid; Khadija Sitabkhan; Karl Mason (ECAI Workshops (2), 2023)

Modelling Electricity Consumption in Irish Dairy Farms Using Agent-Based Modelling. - Hossein Khaleghy; Abdul Wahid; Eoghan Clifford; Karl Mason (ECAI Workshops (2), 2023)

Go-Explore for Residential Energy Management. - Junlin Lu; Patrick Mannion; Karl Mason (ECAI Workshops (2), 2023)

A Multi-agent Systems Approach for Peer-to-Peer Energy Trading in Dairy Farming. - Mian Ibad Ali Shah; Abdul Wahid; Enda Barrett; Karl Mason (ECAI Workshops (2), 2023)

Evolving Neural Networks for Robotic Arm Control. - Anthony Horgan; Karl Mason (EvoApplications@EvoStar, 2023)

Modelling Solar PV Adoption in Irish Dairy Farms Using Agent-Based Modelling. - Iias Faiud; Karl Mason; Michael Schukat (PKDD/ECML Workshops (3), 2023)

Integrating Renewable Energy in Agriculture: A Deep Reinforcement Learning-Based Approach. - Abdul Wahid; Iias Faiud; Karl Mason (PKDD/ECML Workshops (3), 2023)

Inferring Preferences from Demonstrations in Multi-objective Reinforcement Learning: A Dynamic Weight-based Approach. - Junlin Lu; Patrick Mannion; Karl Mason (CoRR, 2023)

Evolutionary Strategy Guided Reinforcement Learning via MultiBuffer Communication. - Adam Callaghan; Karl Mason; Patrick Mannion (CoRR, 2023)

Evolving Multi-Objective Neural Network Controllers for Robot Swarms. - Karl Mason; Sabine Hauert (CoRR, 2023)

Special issue on evolutionary machine learning. - Karl Mason; Patrick Mannion (Knowl. Eng. Rev., 2023)

A Meta-Learning Approach for Multi-Objective Reinforcement Learning in Sustainable Home Energy Management. - Junlin Lu; Patrick Mannion; Karl Mason (ECAI, 2024)

Lo-MARVE: A Low Cost Autonomous Underwater Vehicle for Marine Exploration. - Karl Mason; Daniel Kelly (ICCMA, 2024)

A Deep Reinforcement Learning Approach to Battery Management in Dairy Farming via Proximal Policy Optimization. - Nawazish Ali; Rachael Shaw; Karl Mason (PAAMS, 2024)

Optimal Solar PV Site Identification Using AutoEncoders and Clustering. - Smitesh Patil; Abdul Wahid; Karl Mason (PAAMS (Workshops), 2024)

Reinforcement Learning Enabled Peer-to-Peer Energy Trading for Dairy Farms. - Mian Ibad Ali Shah; Enda Barrett; Karl Mason (PAAMS, 2024)

Optimizing Deep Reinforcement Learning for Adaptive Robotic Arm Control. - Jonaid Shianifar; Michael Schukat; Karl Mason (PAAMS (Workshops), 2024)

Peer-to-peer energy trading in dairy farms using multi-agent systems. - Mian Ibad Ali Shah; Abdul Wahid; Enda Barrett; Karl Mason (Comput. Electr. Eng., 2024)

Inferring Preferences from Demonstrations in Multi-Objective Residential Energy Management. - Junlin Lu; Patrick Mannion; Karl Mason (CoRR, 2024)

A Reinforcement Learning Approach to Dairy Farm Battery Management using Q Learning. - Nawazish Ali; Abdul Wahid; Rachael Shaw; Karl Mason (CoRR, 2024)

A Meta-Learning Approach for Multi-Objective Reinforcement Learning in Sustainable Home Environments. - Junlin Lu; Patrick Mannion; Karl Mason (CoRR, 2024)

Multi-agent systems in Peer-to-Peer energy trading: A comprehensive survey. - Mian Ibad Ali Shah; Abdul Wahid; Enda Barrett; Karl Mason (Eng. Appl. Artif. Intell., 2024)

Demonstration-Guided Multi-Objective Reinforcement Learning. - Junlin Lu; Patrick Mannion; Karl Mason (Trans. Mach. Learn. Res., 2024)

Inferring preferences from demonstrations in multi-objective reinforcement learning. - Junlin Lu; Patrick Mannion; Karl Mason (Neural Comput. Appl., 2024)

Extending Evolution-Guided Policy Gradient Learning into the multi-objective domain. - Adam Callaghan; Karl Mason; Patrick Mannion (Neurocomputing, 2025)

Uncertainty-Aware Knowledge Transformers for Peer-to-Peer Energy Trading with Multi-Agent Reinforcement Learning. - Mian Ibad Ali Shah; Enda Barrett; Karl Mason (CoRR, 2025)