The emergence of cooperation among agents using simple fixed bias tagging. - Enda Howley; Colm O'Riordan (Congress on Evolutionary Computation, 2005)

The Effects and Evolution of Implicit Trust in Populations Playing the Iterated Prisoner's Dilemma. - Enda Howley; Colm O'Riordan (IEEE Congress on Evolutionary Computation, 2006)

The effects of viscosity in choice and refusal IPD environments. - Enda Howley; Colm O'Riordan (Artif. Intell. Rev., 2006)

Agent Interactions and Implicit Trust in IPD Environments. - Enda Howley; Colm O'Riordan (Adaptive Agents and Multi-Agents Systems, 2007)

The Effects of Payoff Preferences on Agent Tolerance. - Enda Howley; Colm O'Riordan (ALIFE, 2008)

Norm Convergence in Populations of Dynamically Interacting Agents. - Declan Mungovan; Enda Howley; Jim Duggan (AICS, 2009)

The Effects of Evolved Sociability in a Commons Dilemma. - Enda Howley; Jim Duggan (ALA, 2009)

Optimisation of the Beer Distribution Game with complex customer demand patterns. - Hongliang Liu; Enda Howley; Jim Duggan (IEEE Congress on Evolutionary Computation, 2009)

Evolving Group Coordination in an N-Player Game. - Enda Barrett; Enda Howley; Jim Duggan (ECAL (1), 2009)

The Impact of Market Preferences on the Evolution of Market Price and Product Quality. - Hongliang Liu; Enda Howley; Jim Duggan (MALLOW, 2010)

Tag-based cooperation in N-player dilemmas. - Enda Howley; Jim Duggan (AAMAS, 2011)

A Learning Architecture for Scheduling Workflow Applications in the Cloud. - Enda Barrett; Enda Howley; Jim Duggan (ECOWS, 2011)

Particle swarm optimisation with gradually increasing directed neighbourhoods. - Hongliang Liu; Enda Howley; Jim Duggan (GECCO, 2011)

Investing in the Commons: a Study of Openness and the Emergence of Cooperation. - Enda Howley; Jim Duggan (Adv. Complex Syst., 2011)

The influence of random interactions and decision heuristics on norm evolution in social networks. - Declan Mungovan; Enda Howley; Jim Duggan (Comput. Math. Organ. Theory, 2011)

Applying reinforcement learning towards automating resource allocation and application scalability in the cloud. - Enda Barrett; Enda Howley; Jim Duggan (Concurr. Comput. Pract. Exp., 2013)

Particle Swarm Optimisation with Enhanced Memory Particles. - Ian Broderick; Enda Howley (ANTS Conference, 2014)

A parallel framework for Bayesian reinforcement learning. - Enda Barrett; Jim Duggan; Enda Howley (Connect. Sci., 2014)

Preface to the special issue: Adaptive Learning Agents, Part 1. - Sam Devlin; Daniel Hennes; Enda Howley (Connect. Sci., 2014)

Preface to the special issue: Adaptive Learning Agents Part 2. - Sam Devlin; Daniel Hennes; Enda Howley (Connect. Sci., 2014)

Parallel Reinforcement Learning for Traffic Signal Control. - Patrick Mannion; Jim Duggan; Enda Howley (ANT/SEIT, 2015)

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

An Experimental Review of Reinforcement Learning Algorithms for Adaptive Traffic Signal Control. - Patrick Mannion; Jim Duggan; Enda Howley (Autonomic Road Transport Support Systems, 2016)

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

An Analytics Framework to Support Surge Capacity Planning for Emerging Epidemics. - Martina Curran; Enda Howley; Jim Duggan (Digital Health, 2016)

An Autonomous Network Aware VM Migration Strategy in Cloud Data Centres. - Martin Duggan; Jim Duggan; Enda Howley; Enda Barrett (ICCAC, 2016)

Deep Reinforcement Learning: An Overview. - Seyed Sajad Mousavi; Michael Schukat; Enda Howley (IntelliSys (2), 2016)

Preface to the special issue: adaptive learning agents. - Peter Vrancx; Enda Howley; Matt Knudson (Knowl. Eng. Rev., 2016)

A Theoretical and Empirical Analysis of Reward Transformations in Multi-Objective Stochastic Games. - Patrick Mannion; Jim Duggan; Enda Howley (AAMAS, 2017)

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)

An advanced reinforcement learning approach for energy-aware virtual machine consolidation in cloud data centers. - Rachael Shaw; Enda Howley; Enda Barrett (ICITST, 2017)

Predicting the Available Bandwidth on Intra Cloud Network Links for Deadline Constrained Workflow Scheduling in Public Clouds. - Rachael Shaw; Enda Howley; Enda Barrett (ICSOC, 2017)

A network aware approach for the scheduling of virtual machine migration during peak loads. - Martin Duggan; Jim Duggan; Enda Howley; Enda Barrett (Clust. Comput., 2017)

Traffic Light Control Using Deep Policy-Gradient and Value-Function Based Reinforcement Learning. - Seyed Sajad Mousavi; Michael Schukat; Peter Corcoran 001; Enda Howley (CoRR, 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)

Multi-agent credit assignment in stochastic resource management games. - Patrick Mannion; Sam Devlin; Jim Duggan; Enda Howley (Knowl. Eng. Rev., 2017)

A reinforcement learning approach for the scheduling of live migration from under utilised hosts. - Martin Duggan; Jim Duggan; Enda Howley; Enda Barrett (Memetic Comput., 2017)

A Predictive Anti-Correlated Virtual Machine Placement Algorithm for Green Cloud Computing. - Rachael Shaw; Enda Howley; Enda Barrett (UCC, 2018)

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)

Reward shaping for knowledge-based multi-objective multi-agent reinforcement learning. - Patrick Mannion; Sam Devlin; Jim Duggan; Enda Howley (Knowl. Eng. Rev., 2018)

An Energy Efficient and Interference Aware Virtual Machine Consolidation Algorithm Using Workload Classification. - Rachael Shaw; Enda Howley; Enda Barrett (ICSOC, 2019)

An energy efficient anti-correlated virtual machine placement algorithm using resource usage predictions. - Rachael Shaw; Enda Howley; Enda Barrett (Simul. Model. Pract. Theory, 2019)

A multitime-steps-ahead prediction approach for scheduling live migration in cloud data centers. - Martin Duggan; Rachael Shaw; Jim Duggan; Enda Howley; Enda Barrett (Softw. Pract. Exp., 2019)

Evolved Gossip Contracts - A Framework for Designing Multi-agent Systems. - Nicola Mc Donnell; Enda Howley; Jim Duggan (PPSN (1), 2020)

Chordomics: a visualization tool for linking function to phylogeny in microbiomes. - Kevin McDonnell; Nicholas Waters; Enda Howley; Florence Abram (Bioinform., 2020)

Dynamic virtual machine consolidation using a multi-agent system to optimise energy efficiency in cloud computing. - Nicola Mc Donnell; Enda Howley; Jim Duggan (Future Gener. Comput. Syst., 2020)

An intelligent ensemble learning approach for energy efficient and interference aware dynamic virtual machine consolidation. - Rachael Shaw; Enda Howley; Enda Barrett (Simul. Model. Pract. Theory, 2020)

Distributional Monte Carlo Tree Search for Risk-Aware and Multi-Objective Reinforcement Learning. - Conor F. Hayes; Mathieu Reymond; Diederik M. Roijers; Enda Howley; Patrick Mannion (AAMAS, 2021)

Risk Aware and Multi-Objective Decision Making with Distributional Monte Carlo Tree Search. - Conor F. Hayes; Mathieu Reymond; Diederik M. Roijers; Enda Howley; Patrick Mannion (CoRR, 2021)

Decision-Theoretic Planning for the Expected Scalarised Returns. - Conor F. Hayes; Diederik M. Roijers; Enda Howley; Patrick Mannion (AAMAS, 2022)

A practical guide to multi-objective reinforcement learning and planning. - Conor F. Hayes; Roxana Radulescu; Eugenio Bargiacchi; Johan Källström; Matthew Macfarlane; Mathieu Reymond; Timothy Verstraeten; Luisa M. Zintgraf; Richard Dazeley; Fredrik Heintz; Enda Howley; Athirai A. Irissappane; et al. (Auton. Agents Multi Agent Syst., 2022)

Applying neural networks to predict HPC-I/O bandwidth over seismic data on lustre file system for ExSeisDat. - Abdul Jabbar Saeed Tipu; Padraig Ó Conbhuí; Enda Howley (Clust. Comput., 2022)

Multi-Objective Coordination Graphs for the Expected Scalarised Returns with Generative Flow Models. - Conor F. Hayes; Timothy Verstraeten; Diederik M. Roijers; Enda Howley; Patrick Mannion (CoRR, 2022)

Applying Reinforcement Learning towards automating energy efficient virtual machine consolidation in cloud data centers. - Rachael Shaw; Enda Howley; Enda Barrett (Inf. Syst., 2022)

A Brief Guide to Multi-Objective Reinforcement Learning and Planning. - Conor F. Hayes; Roxana Radulescu; Eugenio Bargiacchi; Johan Källström; Matthew Macfarlane; Mathieu Reymond; Timothy Verstraeten; Luisa M. Zintgraf; Richard Dazeley; Fredrik Heintz; Enda Howley; Athirai A. Irissappane; et al. (AAMAS, 2023)

Distributional Multi-Objective Decision Making. - Willem Röpke; Conor F. Hayes; Patrick Mannion; Enda Howley; Ann Nowé; Diederik M. Roijers (IJCAI, 2023)

ADT: Agent-based Dynamic Thresholding for Anomaly Detection. - Xue Yang; Enda Howley; Michael Schukat (CoRR, 2023)

Seismic data IO and sorting optimization in HPC through ANNs prediction based auto-tuning for ExSeisDat. - Abdul Jabbar Saeed Tipu; Padraig Ó Conbhuí; Enda Howley (Neural Comput. Appl., 2023)

A Genetic Programming-based Framework for Semi-automated Multi-agent Systems Engineering. - Nicola Mc Donnell; Jim Duggan; Enda Howley (ACM Trans. Auton. Adapt. Syst., 2023)

Monte Carlo tree search algorithms for risk-aware and multi-objective reinforcement learning. - Conor F. Hayes; Mathieu Reymond; Diederik M. Roijers; Enda Howley; Patrick Mannion (Auton. Agents Multi Agent Syst., 2023)

Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning. - Peter Vamplew 001; Cameron Foale; Conor F. Hayes; Patrick Mannion; Enda Howley; Richard Dazeley; Scott Johnson; Johan Källström; Gabriel de Oliveira Ramos; Roxana Radulescu; Willem Röpke; Diederik M. Roijers (AAMAS, 2024)

Artificial neural networks based predictions towards the auto-tuning and optimization of parallel IO bandwidth in HPC system. - Abdul Jabbar Saeed Tipu; Padraig Ó Conbhuí; Enda Howley (Clust. Comput., 2024)

ADT: Time series anomaly detection for cyber-physical systems via deep reinforcement learning. - Xue Yang; Enda Howley; Michael Schukat (Comput. Secur., 2024)

Exploring the Pareto front of multi-objective COVID-19 mitigation policies using reinforcement learning. - Mathieu Reymond; Conor F. Hayes; Lander Willem; Roxana Radulescu; Steven Abrams; Diederik M. Roijers; Enda Howley; Patrick Mannion; Niel Hens; Ann Nowé; Pieter Libin (Expert Syst. Appl., 2024)

Expected scalarised returns dominance: a new solution concept for multi-objective decision making. - Conor F. Hayes; Timothy Verstraeten; Diederik M. Roijers; Enda Howley; Patrick Mannion (Neural Comput. Appl., 2025)

Agent-based dynamic thresholding for adaptive anomaly detection using reinforcement learning. - Xue Yang; Enda Howley; Michael Schukat (Neural Comput. Appl., 2025)