Conor F. Hayes

According to our database, Conor F. Hayes authored at least 20 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Overcoming Forgetting in LLM Fine-Tuning with Evolution Strategies.

Kajetan Schweighofer, Conor F. Hayes, Roberto Dailey, Risto Miikkulainen, Xin Qiu

CoRR, May, 2026

2025

Solving a Million-Step LLM Task with Zero Errors.

Elliot Meyerson, Giuseppe Paolo, Roberto Dailey, Hormoz Shahrzad, Olivier Francon, Conor F. Hayes, Xin Qiu, Babak Hodjat, Risto Miikkulainen

CoRR, November, 2025

Evolution Strategies at Scale: LLM Fine-Tuning Beyond Reinforcement Learning.

Xin Qiu, Yulu Gan, Conor F. Hayes, Qiyao Liang, Elliot Meyerson, Babak Hodjat, Risto Miikkulainen

CoRR, September, 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., July, 2025

Deep Symbolic Optimization: Reinforcement Learning for Symbolic Mathematics.

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

CoRR, May, 2025

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

Multi-objective Reinforcement Learning: A Tool for Pluralistic Alignment.

Peter Vamplew, Conor F. Hayes, Cameron Foale, Richard Dazeley, Hadassah Harland

CoRR, 2024

From Text to Life: On the Reciprocal Relationship between Artificial Life and Large Language Models.

Eleni Nisioti, Claire Glanois, Elias Najarro, Andrew Dai, Elliot Meyerson, Joachim Winther Pedersen, Laetitia Teodorescu, Conor F. Hayes, Shyam Sudhakaran, Sebastian Risi

CoRR, 2024

Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning.

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

Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

2023

Actor-critic multi-objective reinforcement learning for non-linear utility functions.

Mathieu Reymond, Conor F. Hayes, Denis Steckelmacher, Diederik M. Roijers, Ann Nowé

Auton. Agents Multi Agent Syst., October, 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., October, 2023

Distributional Multi-Objective Decision Making.

Willem Röpke, Conor F. Hayes, Patrick Mannion, Enda Howley, Ann Nowé, Diederik M. Roijers

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 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, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

Scalar Reward is Not Enough.

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

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

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

Scalar reward is not enough: a response to Silver, Singh, Precup and Sutton (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

Auton. Agents Multi Agent Syst., 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, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers

Auton. Agents Multi Agent Syst., 2022

Decision-Theoretic Planning for the Expected Scalarised Returns.

Conor F. Hayes, Diederik M. Roijers, Enda Howley, Patrick Mannion

Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

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

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

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021