Patrick Mannion

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 57

Top Topics

Reinforcement Learning

Stochastic Games

Top Venues

Knowl. Eng. Rev.

Auton. Agents Multi Agent Syst.

Publications

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
Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning. CoRR (2024)
Junlin Lu, Patrick Mannion, Karl Mason
Demonstration Guided Multi-Objective Reinforcement Learning. CoRR (2024)
Junlin Lu, Patrick Mannion, Karl Mason
Go-Explore for Residential Energy Management. CoRR (2024)
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
Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning. AAMAS (2024)
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, Roxana Radulescu
MOMAland: A Set of Benchmarks for Multi-Objective Multi-Agent Reinforcement Learning. CoRR (2024)
Junlin Lu, Patrick Mannion, Karl Mason
A Meta-Learning Approach for Multi-Objective Reinforcement Learning in Sustainable Home Environments. CoRR (2024)
Mathieu Reymond, Conor F. Hayes, Lander Willem, Roxana Radulescu, Steven Abrams, Diederik M. Roijers, Enda Howley, Patrick Mannion, Niel Hens, Ann Nowé, Pieter Libin
Exploring the Pareto front of multi-objective COVID-19 mitigation policies using reinforcement learning. Expert Syst. Appl. 249 (2024)
Willem Röpke, Mathieu Reymond, Patrick Mannion, Diederik M. Roijers, Ann Nowé, Roxana Radulescu
Divide and Conquer: Provably Unveiling the Pareto Front with Multi-Objective Reinforcement Learning. CoRR (2024)
Junlin Lu, Patrick Mannion, Karl Mason
Inferring Preferences from Demonstrations in Multi-Objective Residential Energy Management. CoRR (2024)
Willem Röpke, Conor F. Hayes, Patrick Mannion, Enda Howley, Ann Nowé, Diederik M. Roijers
Distributional Multi-Objective Decision Making. IJCAI (2023)
Karl Mason, Patrick Mannion
Special issue on evolutionary machine learning. Knowl. Eng. Rev. 38 (2023)
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
A Brief Guide to Multi-Objective Reinforcement Learning and Planning. AAMAS (2023)
Seán Caulfield Curley, Karl Mason, Patrick Mannion
Know Your Enemy: Identifying and Adapting to Adversarial Attacks in Deep Reinforcement Learning. AAMAS (2023)
Willem Röpke, Conor F. Hayes, Patrick Mannion, Enda Howley, Ann Nowé, Diederik M. Roijers
Distributional Multi-Objective Decision Making. CoRR (2023)
Conor F. Hayes, Mathieu Reymond, Diederik M. Roijers, Enda Howley, Patrick Mannion
Monte Carlo tree search algorithms for risk-aware and multi-objective reinforcement learning. Auton. Agents Multi Agent Syst. 37 (2) (2023)
Seán Caulfield Curley, Karl Mason, Patrick Mannion
Know Your Enemy: Identifying Adversarial Behaviours in Deep Reinforcement Learning Agents (Student Abstract). AAAI (2023)
Adam Callaghan, Karl Mason, Patrick Mannion
Evolutionary Strategy Guided Reinforcement Learning via MultiBuffer Communication. CoRR (2023)
Junlin Lu, Patrick Mannion, Karl Mason
Go-Explore for Residential Energy Management. ECAI Workshops (2) (2023)
Junlin Lu, Patrick Mannion, Karl Mason
Inferring Preferences from Demonstrations in Multi-objective Reinforcement Learning: A Dynamic Weight-based Approach. CoRR (2023)
Peter Vamplew, 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
Scalar Reward is Not Enough. AAMAS (2023)
Conor F. Hayes, Diederik M. Roijers, Enda Howley, Patrick Mannion
Decision-Theoretic Planning for the Expected Scalarised Returns. AAMAS (2022)
Roxana Radulescu, Timothy Verstraeten, Yijie Zhang, Patrick Mannion, Diederik M. Roijers, Ann Nowé
Opponent learning awareness and modelling in multi-objective normal form games. Neural Comput. Appl. 34 (3) (2022)
Felipe Leno da Silva, Patrick MacAlpine, Roxana Radulescu, Fernando P. Santos, Patrick Mannion
Special issue on adaptive and learning agents 2020. Neural Comput. Appl. 34 (3) (2022)
Peter Vamplew, 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
Scalar reward is not enough: a response to Silver, Singh, Precup and Sutton (2021). Auton. Agents Multi Agent Syst. 36 (2) (2022)
Conor F. Hayes, Mathieu Reymond, Diederik M. Roijers, Enda Howley, Patrick Mannion
Monte Carlo Tree Search Algorithms for Risk-Aware and Multi-Objective Reinforcement Learning. CoRR (2022)
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
A practical guide to multi-objective reinforcement learning and planning. Auton. Agents Multi Agent Syst. 36 (1) (2022)
B. Ravi Kiran, Ibrahim Sobh, Victor Talpaert, Patrick Mannion, Ahmad A. Al Sallab, Senthil Kumar Yogamani, Patrick Pérez
Deep Reinforcement Learning for Autonomous Driving: A Survey. IEEE Trans. Intell. Transp. Syst. 23 (6) (2022)
Mathieu Reymond, Conor F. Hayes, Lander Willem, Roxana Radulescu, Steven Abrams, Diederik M. Roijers, Enda Howley, Patrick Mannion, Niel Hens, Ann Nowé, Pieter Libin
Exploring the Pareto front of multi-objective COVID-19 mitigation policies using reinforcement learning. CoRR (2022)
Conor F. Hayes, Timothy Verstraeten, Diederik M. Roijers, Enda Howley, Patrick Mannion
Multi-Objective Coordination Graphs for the Expected Scalarised Returns with Generative Flow Models. CoRR (2022)
David O'Callaghan, Patrick Mannion
Exploring the Impact of Tunable Agents in Sequential Social Dilemmas. CoRR (2021)
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
A Practical Guide to Multi-Objective Reinforcement Learning and Planning. CoRR (2021)
Peter Vamplew, 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
Scalar reward is not enough: A response to Silver, Singh, Precup and Sutton (2021). CoRR (2021)
Conor F. Hayes, Timothy Verstraeten, Diederik M. Roijers, Enda Howley, Patrick Mannion
Expected Scalarised Returns Dominance: A New Solution Concept for Multi-Objective Decision Making. CoRR (2021)
Conor F. Hayes, Mathieu Reymond, Diederik M. Roijers, Enda Howley, Patrick Mannion
Distributional Monte Carlo Tree Search for Risk-Aware and Multi-Objective Reinforcement Learning. AAMAS (2021)
Conor F. Hayes, Mathieu Reymond, Diederik M. Roijers, Enda Howley, Patrick Mannion
Risk Aware and Multi-Objective Decision Making with Distributional Monte Carlo Tree Search. CoRR (2021)
David O'Callaghan, Patrick Mannion
Tunable Behaviours in Sequential Social Dilemmas using Multi-Objective Reinforcement Learning. AAMAS (2021)
Patrick Mannion, Anna Harutyunyan, Bei Peng, Kaushik Subramanian
Special issue on adaptive and learning agents 2018. Knowl. Eng. Rev. 36 (2021)
Roxana Radulescu, Patrick Mannion, Diederik M. Roijers, Ann Nowé
Multi-Objective Multi-Agent Decision Making: A Utility-based Analysis and Survey. AAMAS (2020)
Roxana Radulescu, Timothy Verstraeten, Yijie Zhang, Patrick Mannion, Diederik M. Roijers, Ann Nowé
Opponent Learning Awareness and Modelling in Multi-Objective Normal Form Games. CoRR (2020)
Roxana Radulescu, Patrick Mannion, Yijie Zhang, Diederik M. Roijers, Ann Nowé
A utility-based analysis of equilibria in multi-objective normal form games. CoRR (2020)
Yijie Zhang, Roxana Radulescu, Patrick Mannion, Diederik M. Roijers, Ann Nowé
Opponent Modelling for Reinforcement Learning in Multi-Objective Normal Form Games. AAMAS (2020)
Roxana Radulescu, Patrick Mannion, Diederik M. Roijers, Ann Nowé
Multi-objective multi-agent decision making: a utility-based analysis and survey. Auton. Agents Multi Agent Syst. 34 (1) (2020)
Patrick Mannion, Patrick MacAlpine, Bei Peng, Roxana Radulescu
Special issue on adaptive and learning agents 2019. Knowl. Eng. Rev. 35 (2020)
Roxana Radulescu, Patrick Mannion, Yijie Zhang, Diederik M. Roijers, Ann Nowé
A utility-based analysis of equilibria in multi-objective normal-form games. Knowl. Eng. Rev. 35 (2020)
Bangalore Ravi Kiran, Ibrahim Sobh, Victor Talpaert, Patrick Mannion, Ahmad A. Al Sallab, Senthil Kumar Yogamani, Patrick Pérez
Deep Reinforcement Learning for Autonomous Driving: A Survey. CoRR (2020)
Victor Talpaert, Ibrahim Sobh, B. Ravi Kiran, Patrick Mannion, Senthil Kumar Yogamani, Ahmad El Sallab, Patrick Pérez
Exploring Applications of Deep Reinforcement Learning for Real-world Autonomous Driving Systems. VISIGRAPP (5: VISAPP) (2019)
Golden Rockefeller, Patrick Mannion, Kagan Tumer
Curriculum Learning for Tightly Coupled Multiagent Systems. AAMAS (2019)
Patrick Mannion
Vulnerable road user detection: state-of-the-art and open challenges. CoRR (2019)
Victor Talpaert, Ibrahim Sobh, B. Ravi Kiran, Patrick Mannion, Senthil Kumar Yogamani, Ahmad El Sallab, Patrick Pérez
Exploring applications of deep reinforcement learning for real-world autonomous driving systems. CoRR (2019)
Roxana Radulescu, Patrick Mannion, Diederik M. Roijers, Ann Nowé
Multi-Objective Multi-Agent Decision Making: A Utility-based Analysis and Survey. CoRR (2019)
Golden Rockefeller, Patrick Mannion, Kagan Tumer
Fitness Critics for Multiagent Learning: Extended Abstract. MRS (2019)
Patrick Mannion, Sam Devlin, Jim Duggan, Enda Howley
Reward shaping for knowledge-based multi-objective multi-agent reinforcement learning. Knowl. Eng. Rev. 33 (2018)
Patrick Mannion, Anna Harutyunyan, Kaushik Subramanian
Special issue on adaptive and learning agents 2017. Knowl. Eng. Rev. 33 (2018)
Patrick Mannion, Sam Devlin, Karl Mason, Jim Duggan, Enda Howley
Policy invariance under reward transformations for multi-objective reinforcement learning. Neurocomputing 263 (2017)
Patrick Mannion, Sam Devlin, Jim Duggan, Enda Howley
Multi-agent credit assignment in stochastic resource management games. Knowl. Eng. Rev. 32 (2017)
Patrick Mannion, Jim Duggan, Enda Howley
A Theoretical and Empirical Analysis of Reward Transformations in Multi-Objective Stochastic Games. AAMAS (2017)
Patrick Mannion, Karl Mason, Sam Devlin, Jim Duggan, Enda Howley
Multi-Objective Dynamic Dispatch Optimisation using Multi-Agent Reinforcement Learning: (Extended Abstract). AAMAS (2016)
Patrick Mannion, Jim Duggan, Enda Howley
Parallel Reinforcement Learning for Traffic Signal Control. ANT/SEIT (2015)
Patrick Mannion
Integrating UWB in consumer devices. CCNC (2006)