Integrating UWB in consumer devices. - Patrick Mannion (CCNC, 2006)

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

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

Policy invariance under reward transformations for multi-objective reinforcement learning. - Patrick Mannion; Sam Devlin; 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)

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

Special issue on adaptive and learning agents 2017. - Patrick Mannion; Anna Harutyunyan; Kaushik Subramanian (Knowl. Eng. Rev., 2018)

Curriculum Learning for Tightly Coupled Multiagent Systems. - Golden Rockefeller; Patrick Mannion; Kagan Tumer (AAMAS, 2019)

Fitness Critics for Multiagent Learning: Extended Abstract. - Golden Rockefeller; Patrick Mannion; Kagan Tumer (MRS, 2019)

Exploring Applications of Deep Reinforcement Learning for Real-world Autonomous Driving Systems. - Victor Talpaert; Ibrahim Sobh; B. Ravi Kiran 001; Patrick Mannion; Senthil Kumar Yogamani; Ahmad El Sallab; Patrick Pérez (VISIGRAPP (5: VISAPP), 2019)

Vulnerable road user detection: state-of-the-art and open challenges. - Patrick Mannion (CoRR, 2019)

Opponent Modelling for Reinforcement Learning in Multi-Objective Normal Form Games. - Yijie Zhang; Roxana Radulescu; Patrick Mannion; Diederik M. Roijers; Ann Nowé (AAMAS, 2020)

Multi-objective multi-agent decision making: a utility-based analysis and survey. - Roxana Radulescu; Patrick Mannion; Diederik M. Roijers; Ann Nowé (Auton. Agents Multi Agent Syst., 2020)

Special issue on adaptive and learning agents 2019. - Patrick Mannion; Patrick MacAlpine; Bei Peng 001; Roxana Radulescu (Knowl. Eng. Rev., 2020)

A utility-based analysis of equilibria in multi-objective normal-form games. - Roxana Radulescu; Patrick Mannion; Yijie Zhang; Diederik M. Roijers; Ann Nowé (Knowl. Eng. Rev., 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)

Tunable Behaviours in Sequential Social Dilemmas using Multi-Objective Reinforcement Learning. - David O'Callaghan; Patrick Mannion (AAMAS, 2021)

Exploring the Impact of Tunable Agents in Sequential Social Dilemmas. - David O'Callaghan; Patrick Mannion (CoRR, 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)

Special issue on adaptive and learning agents 2018. - Patrick Mannion; Anna Harutyunyan; Bei Peng 001; Kaushik Subramanian (Knowl. Eng. Rev., 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)

Scalar reward is not enough: a response to Silver, Singh, Precup and Sutton (2021). - Peter Vamplew 001; Benjamin J. Smith; Johan Källström; Gabriel de Oliveira Ramos; Roxana Radulescu; Diederik M. Roijers; Conor F. Hayes; Fredrik Heintz; Patrick Mannion; Pieter J. K. Libin; Richard Dazeley; Cameron Foale (Auton. Agents Multi Agent Syst., 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)

Opponent learning awareness and modelling in multi-objective normal form games. - Roxana Radulescu; Timothy Verstraeten; Yijie Zhang; Patrick Mannion; Diederik M. Roijers; Ann Nowé (Neural Comput. Appl., 2022)

Special issue on adaptive and learning agents 2020. - Felipe Leno da Silva; Patrick MacAlpine; Roxana Radulescu; Fernando P. Santos; Patrick Mannion (Neural Comput. Appl., 2022)

Deep Reinforcement Learning for Autonomous Driving: A Survey. - B. Ravi Kiran 001; Ibrahim Sobh; Victor Talpaert; Patrick Mannion; Ahmad A. Al Sallab; Senthil Kumar Yogamani; Patrick Pérez (IEEE Trans. Intell. Transp. Syst., 2022)

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

Scalar Reward is Not Enough. - Peter Vamplew 001; Benjamin J. Smith; Johan Källström; Gabriel de Oliveira Ramos; Roxana Radulescu; Diederik M. Roijers; Conor F. Hayes; Friedrik Hentz; Patrick Mannion; Pieter J. K. Libin; Richard Dazeley; Cameron Foale (AAMAS, 2023)

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

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)

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

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

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

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

Learning in Multi-Objective Public Goods Games with Non-Linear Utilities. - Nicole Orzan; Erman Acar; Davide Grossi; Patrick Mannion; Roxana Radulescu (ECAI, 2024)

Inferring Preferences from Demonstrations in Multi-Objective Residential Energy Management. - Junlin Lu; Patrick Mannion; 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)

MOMAland: A Set of Benchmarks for Multi-Objective Multi-Agent Reinforcement Learning. - Florian Felten; Umut Ucak; Hicham Azmani; Gao Peng; Willem Röpke; Hendrik Baier; Patrick Mannion; Diederik M. Roijers; Jordan K. Terry; El-Ghazali Talbi; Grégoire Danoy; Ann Nowé; et al. (CoRR, 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)

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)

Divide and Conquer: Provably Unveiling the Pareto Front with Multi-Objective Reinforcement Learning. - Willem Röpke; Mathieu Reymond; Patrick Mannion; Diederik M. Roijers; Ann Nowé; Roxana Radulescu (AAMAS, 2025)

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

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)