Enda Howley - RankMe

78 papers A* 1A 10B 3C 1Misc 1Journal 44Unranked 17

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Agent-based dynamic thresholding for adaptive anomaly detection using reinforcement learning. Neural Comput. Appl. Xue Yang, Enda Howley, Michael Schukat
2025	J	`jnl`	Demonstration-Guided Continual Reinforcement Learning in Dynamic Environments. CoRR Xue Yang, Michael Schukat, Junlin Lu, Patrick Mannion, Karl Mason, Enda Howley
2025	J	`jnl`	Expected scalarised returns dominance: a new solution concept for multi-objective decision making. Neural Comput. Appl. Conor F. Hayes, Timothy Verstraeten, Diederik M. Roijers, Enda Howley, Patrick Mannion
2024	J	`jnl`	ADT: Time series anomaly detection for cyber-physical systems via deep reinforcement learning. Comput. Secur. Xue Yang, Enda Howley, Michael Schukat
2024	J	`jnl`	Artificial neural networks based predictions towards the auto-tuning and optimization of parallel IO bandwidth in HPC system. Clust. Comput. Abdul Jabbar Saeed Tipu, Padraig Ó Conbhuí, Enda Howley
2024	J	`jnl`	Exploring the Pareto front of multi-objective COVID-19 mitigation policies using reinforcement learning. Expert Syst. Appl. Mathieu Reymond, Conor F. Hayes, Lander Willem, Roxana Radulescu, Steven Abrams, Diederik M. Roijers, Enda Howley, Patrick Mannion, Niel Hens, Ann Nowé, Pieter Libin
2024	A	`conf`	Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning. AAMAS Peter Vamplew, 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
2024	J	`jnl`	Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning. CoRR Peter Vamplew, 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
2023	A	`conf`	A Brief Guide to Multi-Objective Reinforcement Learning and Planning. AAMAS 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, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers
2023	J	`jnl`	A Genetic Programming-based Framework for Semi-automated Multi-agent Systems Engineering. ACM Trans. Auton. Adapt. Syst. Nicola Mc Donnell, Jim Duggan, Enda Howley
2023	J	`jnl`	ADT: Agent-based Dynamic Thresholding for Anomaly Detection. CoRR Xue Yang, Enda Howley, Michael Schukat
2023	A*	`conf`	Distributional Multi-Objective Decision Making. IJCAI Willem Röpke, Conor F. Hayes, Patrick Mannion, Enda Howley, Ann Nowé, Diederik M. Roijers
2023	J	`jnl`	Distributional Multi-Objective Decision Making. CoRR Willem Röpke, Conor F. Hayes, Patrick Mannion, Enda Howley, Ann Nowé, Diederik M. Roijers
2023	J	`jnl`	Monte Carlo tree search algorithms for risk-aware and multi-objective reinforcement learning. Auton. Agents Multi Agent Syst. Conor F. Hayes, Mathieu Reymond, Diederik M. Roijers, Enda Howley, Patrick Mannion
2023	J	`jnl`	Seismic data IO and sorting optimization in HPC through ANNs prediction based auto-tuning for ExSeisDat. Neural Comput. Appl. Abdul Jabbar Saeed Tipu, Padraig Ó Conbhuí, Enda Howley
2022	J	`jnl`	A practical guide to multi-objective reinforcement learning and planning. Auton. Agents Multi Agent Syst. 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, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers
2022	J	`jnl`	Applying Reinforcement Learning towards automating energy efficient virtual machine consolidation in cloud data centers. Inf. Syst. Rachael Shaw, Enda Howley, Enda Barrett
2022	J	`jnl`	Applying neural networks to predict HPC-I/O bandwidth over seismic data on lustre file system for ExSeisDat. Clust. Comput. Abdul Jabbar Saeed Tipu, Padraig Ó Conbhuí, Enda Howley
2022	A	`conf`	Decision-Theoretic Planning for the Expected Scalarised Returns. AAMAS Conor F. Hayes, Diederik M. Roijers, Enda Howley, Patrick Mannion
2022	J	`jnl`	Exploring the Pareto front of multi-objective COVID-19 mitigation policies using reinforcement learning. CoRR Mathieu Reymond, Conor F. Hayes, Lander Willem, Roxana Radulescu, Steven Abrams, Diederik M. Roijers, Enda Howley, Patrick Mannion, Niel Hens, Ann Nowé, Pieter Libin
2022	J	`jnl`	Monte Carlo Tree Search Algorithms for Risk-Aware and Multi-Objective Reinforcement Learning. CoRR Conor F. Hayes, Mathieu Reymond, Diederik M. Roijers, Enda Howley, Patrick Mannion
2022	J	`jnl`	Multi-Objective Coordination Graphs for the Expected Scalarised Returns with Generative Flow Models. CoRR Conor F. Hayes, Timothy Verstraeten, Diederik M. Roijers, Enda Howley, Patrick Mannion
2021	J	`jnl`	A Practical Guide to Multi-Objective Reinforcement Learning and Planning. CoRR 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, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers
2021	A	`conf`	Distributional Monte Carlo Tree Search for Risk-Aware and Multi-Objective Reinforcement Learning. AAMAS Conor F. Hayes, Mathieu Reymond, Diederik M. Roijers, Enda Howley, Patrick Mannion
2021	J	`jnl`	Expected Scalarised Returns Dominance: A New Solution Concept for Multi-Objective Decision Making. CoRR Conor F. Hayes, Timothy Verstraeten, Diederik M. Roijers, Enda Howley, Patrick Mannion
2021	J	`jnl`	Risk Aware and Multi-Objective Decision Making with Distributional Monte Carlo Tree Search. CoRR Conor F. Hayes, Mathieu Reymond, Diederik M. Roijers, Enda Howley, Patrick Mannion
2020	J	`jnl`	An intelligent ensemble learning approach for energy efficient and interference aware dynamic virtual machine consolidation. Simul. Model. Pract. Theory Rachael Shaw, Enda Howley, Enda Barrett
2020	J	`jnl`	Chordomics: a visualization tool for linking function to phylogeny in microbiomes. Bioinform. Kevin McDonnell, Nicholas Waters, Enda Howley, Florence Abram
2020	J	`jnl`	Dynamic virtual machine consolidation using a multi-agent system to optimise energy efficiency in cloud computing. Future Gener. Comput. Syst. Nicola Mc Donnell, Enda Howley, Jim Duggan
2020	—	`conf`	Evolved Gossip Contracts - A Framework for Designing Multi-agent Systems. PPSN (1) Nicola Mc Donnell, Enda Howley, Jim Duggan
2019	J	`jnl`	A multitime-steps-ahead prediction approach for scheduling live migration in cloud data centers. Softw. Pract. Exp. Martin Duggan, Rachael Shaw, Jim Duggan, Enda Howley, Enda Barrett
2019	A	`conf`	An Energy Efficient and Interference Aware Virtual Machine Consolidation Algorithm Using Workload Classification. ICSOC Rachael Shaw, Enda Howley, Enda Barrett
2019	J	`jnl`	An energy efficient anti-correlated virtual machine placement algorithm using resource usage predictions. Simul. Model. Pract. Theory Rachael Shaw, Enda Howley, Enda Barrett
2018	Misc	`conf`	A Predictive Anti-Correlated Virtual Machine Placement Algorithm for Green Cloud Computing. UCC Rachael Shaw, Enda Howley, Enda Barrett
2018	J	`jnl`	A meta optimisation analysis of particle swarm optimisation velocity update equations for watershed management learning. Appl. Soft Comput. Karl Mason, Jim Duggan, Enda Howley
2018	J	`jnl`	Deep Reinforcement Learning: An Overview. CoRR Seyed Sajad Mousavi, Michael Schukat, Enda Howley
2018	J	`jnl`	Predicting host CPU utilization in the cloud using evolutionary neural networks. Future Gener. Comput. Syst. Karl Mason, Martin Duggan, Enda Barrett, Jim Duggan, Enda Howley
2018	J	`jnl`	Reward shaping for knowledge-based multi-objective multi-agent reinforcement learning. Knowl. Eng. Rev. Patrick Mannion, Sam Devlin, Jim Duggan, Enda Howley
2017	A	`conf`	A Theoretical and Empirical Analysis of Reward Transformations in Multi-Objective Stochastic Games. AAMAS Patrick Mannion, Jim Duggan, Enda Howley
2017	J	`jnl`	A network aware approach for the scheduling of virtual machine migration during peak loads. Clust. Comput. Martin Duggan, Jim Duggan, Enda Howley, Enda Barrett
2017	J	`jnl`	A reinforcement learning approach for the scheduling of live migration from under utilised hosts. Memetic Comput. Martin Duggan, Jim Duggan, Enda Howley, Enda Barrett
2017	—	`conf`	An advanced reinforcement learning approach for energy-aware virtual machine consolidation in cloud data centers. ICITST Rachael Shaw, Enda Howley, Enda Barrett
2017	—	`conf`	Evolving multi-objective neural networks using differential evolution for dynamic economic emission dispatch. GECCO (Companion) Karl Mason, Jim Duggan, Enda Howley
2017	J	`jnl`	Multi-agent credit assignment in stochastic resource management games. Knowl. Eng. Rev. Patrick Mannion, Sam Devlin, Jim Duggan, Enda Howley
2017	J	`jnl`	Multi-objective dynamic economic emission dispatch using particle swarm optimisation variants. Neurocomputing Karl Mason, Jim Duggan, Enda Howley
2017	—	`conf`	Neural network topology and weight optimization through neuro differential evolution. GECCO (Companion) Karl Mason, Jim Duggan, Enda Howley
2017	J	`jnl`	Policy invariance under reward transformations for multi-objective reinforcement learning. Neurocomputing Patrick Mannion, Sam Devlin, Karl Mason, Jim Duggan, Enda Howley
2017	—	`conf`	Predicting host CPU utilization in cloud computing using recurrent neural networks. ICITST Martin Duggan, Karl Mason, Jim Duggan, Enda Howley, Enda Barrett
2017	A	`conf`	Predicting the Available Bandwidth on Intra Cloud Network Links for Deadline Constrained Workflow Scheduling in Public Clouds. ICSOC Rachael Shaw, Enda Howley, Enda Barrett
2017	J	`jnl`	Traffic Light Control Using Deep Policy-Gradient and Value-Function Based Reinforcement Learning. CoRR Seyed Sajad Mousavi, Michael Schukat, Peter Corcoran, Enda Howley
2016	—	`conf`	An Analytics Framework to Support Surge Capacity Planning for Emerging Epidemics. Digital Health Martina Curran, Enda Howley, Jim Duggan
2016	—	`conf`	An Autonomous Network Aware VM Migration Strategy in Cloud Data Centres. ICCAC Martin Duggan, Jim Duggan, Enda Howley, Enda Barrett
2016	—	`ch.`	An Experimental Review of Reinforcement Learning Algorithms for Adaptive Traffic Signal Control. Autonomic Road Transport Support Systems Patrick Mannion, Jim Duggan, Enda Howley
2016	—	`conf`	Deep Reinforcement Learning: An Overview. IntelliSys (2) Seyed Sajad Mousavi, Michael Schukat, Enda Howley
2016	A	`conf`	Multi-Objective Dynamic Dispatch Optimisation using Multi-Agent Reinforcement Learning: (Extended Abstract). AAMAS Patrick Mannion, Karl Mason, Sam Devlin, Jim Duggan, Enda Howley
2016	J	`jnl`	Preface to the special issue: adaptive learning agents. Knowl. Eng. Rev. Peter Vrancx, Enda Howley, Matt Knudson
2015	—	`conf`	Avoidance Strategies in Particle Swarm Optimisation. MENDEL Karl Mason, Enda Howley
2015	—	`conf`	Parallel Reinforcement Learning for Traffic Signal Control. ANT/SEIT Patrick Mannion, Jim Duggan, Enda Howley
2014	J	`jnl`	A parallel framework for Bayesian reinforcement learning. Connect. Sci. Enda Barrett, Jim Duggan, Enda Howley
2014	—	`conf`	Particle Swarm Optimisation with Enhanced Memory Particles. ANTS Conference Ian Broderick, Enda Howley
2014	J	`jnl`	Preface to the special issue: Adaptive Learning Agents Part 2. Connect. Sci. Sam Devlin, Daniel Hennes, Enda Howley
2014	J	`jnl`	Preface to the special issue: Adaptive Learning Agents, Part 1. Connect. Sci. Sam Devlin, Daniel Hennes, Enda Howley
2013	J	`jnl`	Applying reinforcement learning towards automating resource allocation and application scalability in the cloud. Concurr. Comput. Pract. Exp. Enda Barrett, Enda Howley, Jim Duggan
2011	—	`conf`	A Learning Architecture for Scheduling Workflow Applications in the Cloud. ECOWS Enda Barrett, Enda Howley, Jim Duggan
2011	J	`jnl`	Investing in the Commons: a Study of Openness and the Emergence of Cooperation. Adv. Complex Syst. Enda Howley, Jim Duggan
2011	A	`conf`	Particle swarm optimisation with gradually increasing directed neighbourhoods. GECCO Hongliang Liu, Enda Howley, Jim Duggan
2011	A	`conf`	Tag-based cooperation in N-player dilemmas. AAMAS Enda Howley, Jim Duggan
2011	J	`jnl`	The influence of random interactions and decision heuristics on norm evolution in social networks. Comput. Math. Organ. Theory Declan Mungovan, Enda Howley, Jim Duggan
2010	—	`conf`	The Impact of Market Preferences on the Evolution of Market Price and Product Quality. MALLOW Hongliang Liu, Enda Howley, Jim Duggan
2009	—	`conf`	Evolving Group Coordination in an N-Player Game. ECAL (1) Enda Barrett, Enda Howley, Jim Duggan
2009	—	`conf`	Norm Convergence in Populations of Dynamically Interacting Agents. AICS Declan Mungovan, Enda Howley, Jim Duggan
2009	B	`conf`	Optimisation of the Beer Distribution Game with complex customer demand patterns. IEEE Congress on Evolutionary Computation Hongliang Liu, Enda Howley, Jim Duggan
2009	—	`conf`	The Effects of Evolved Sociability in a Commons Dilemma. ALA Enda Howley, Jim Duggan
2008	C	`conf`	The Effects of Payoff Preferences on Agent Tolerance. ALIFE Enda Howley, Colm O'Riordan
2007	—	`conf`	Agent Interactions and Implicit Trust in IPD Environments. Adaptive Agents and Multi-Agents Systems Enda Howley, Colm O'Riordan
2006	B	`conf`	The Effects and Evolution of Implicit Trust in Populations Playing the Iterated Prisoner's Dilemma. IEEE Congress on Evolutionary Computation Enda Howley, Colm O'Riordan
2006	J	`jnl`	The effects of viscosity in choice and refusal IPD environments. Artif. Intell. Rev. Enda Howley, Colm O'Riordan
2005	B	`conf`	The emergence of cooperation among agents using simple fixed bias tagging. Congress on Evolutionary Computation Enda Howley, Colm O'Riordan