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ORCIDConor F. Hayes
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2020 – today
- 2025
[j6]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. Neural Comput. Appl. 37(19): 13079-13099 (2025)- [i12]Conor F. Hayes, Felipe Leno da Silva, Jiachen Yang, T. Nathan Mundhenk, Chak Shing Lee, Jacob F. Pettit, Claudio Santiago, Sookyung Kim, Joanne Taery Kim, Ignacio Aravena Solis, Ruben Glatt, Andre R. Goncalves, Alexander Ladd, Ahmet Can Solak, Thomas Desautels, Daniel M. Faissol, Brenden K. Petersen, Mikel Landajuela:
Deep Symbolic Optimization: Reinforcement Learning for Symbolic Mathematics. CoRR abs/2505.10762 (2025) - 2024
- [j5]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: 123686 (2024) - [c6]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: 2717-2721 - [i11]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 abs/2402.02665 (2024) - [i10]Eleni Nisioti, Claire Glanois, Elias Najarro, Andrew Dai, Elliot Meyerson, Joachim Winther Pedersen, Laetitia Teodorescu, Conor F. Hayes, Shyam Sudhakaran, Sebastian Risi:
From Text to Life: On the Reciprocal Relationship between Artificial Life and Large Language Models. CoRR abs/2407.09502 (2024) - [i9]Peter Vamplew, Conor F. Hayes, Cameron Foale, Richard Dazeley, Hadassah Harland:
Multi-objective Reinforcement Learning: A Tool for Pluralistic Alignment. CoRR abs/2410.11221 (2024) - 2023
- [j4]Mathieu Reymond, Conor F. Hayes, Denis Steckelmacher, Diederik M. Roijers, Ann Nowé:
Actor-critic multi-objective reinforcement learning for non-linear utility functions. Auton. Agents Multi Agent Syst. 37(2): 23 (2023) - [j3]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): 26 (2023) - [c5]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: 839-841 - [c4]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: 1988-1990 - [c3]Willem Röpke, Conor F. Hayes, Patrick Mannion, Enda Howley, Ann Nowé, Diederik M. Roijers:
Distributional Multi-Objective Decision Making. IJCAI 2023: 5711-5719 - [i8]Willem Röpke, Conor F. Hayes, Patrick Mannion, Enda Howley, Ann Nowé, Diederik M. Roijers:
Distributional Multi-Objective Decision Making. CoRR abs/2305.05560 (2023) - 2022
- [j2]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): 26 (2022) - [j1]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): 41 (2022) - [c2]Conor F. Hayes, Diederik M. Roijers, Enda Howley, Patrick Mannion:
Decision-Theoretic Planning for the Expected Scalarised Returns. AAMAS 2022: 1621-1623 - [i7]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 abs/2204.05027 (2022) - [i6]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 abs/2207.00368 (2022) - [i5]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 abs/2211.13032 (2022) - 2021
- [c1]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: 1530-1532 - [i4]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 abs/2102.00966 (2021) - [i3]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 abs/2103.09568 (2021) - [i2]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 abs/2106.01048 (2021) - [i1]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 abs/2112.15422 (2021)
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