Publications

Conference Papers

Distributional Monte Carlo Tree Search for Risk-Aware and Multi-Objective Reinforcement Learning. Conor F. Hayes, Mathieu Reymond, Diederik M. Roijers, Enda Howley and Patrick Mannion. Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS). 2021. [pdf] [poster] 

Workshop Papers

Actor-Critic Multi-Objective Reinforcement Learning for Non-Linear Utility Functions. Mathieu Reymond, Conor F. Hayes, Diederik M. Roijers, Denis Steckelmacher and Ann Nowé. The Multi-Objective Decision Making Workshop 2021. [pdf]

Risk-Aware and Multi-Objective Decision Making with Distributional Monte Carlo Tree Search. Conor F. Hayes, Mathieu Reymond, Diederik M. Roijers, Enda Howley and Patrick Mannion. The Adaptive Learning Agents Workshop 2021 at AAMAS. 2021. [pdf] 

Dominance Criteria and Solution Sets for the Expected Scalarised Returns. Conor F. Hayes, Timothy Verstraeten, Diederik M. Roijers, Enda Howley and Patrick Mannion. The Adaptive Learning Agents Workshop 2021 at AAMAS. 2021. [pdf]

Dynamic Thresholded Lexicographic Ordering.  Conor F. Hayes, Enda Howley and Patrick Mannion. The Adaptive Learning Agents Workshop 2020 at AAMAS. 2020. [pdf]

Preprints

Expected Scalarised Returns Dominance: A New Solution Concept for Multi-Objective Decision Making. Conor F. Hayes, Timothy Verstraeten, Diederik M. Roijers, Enda Howley and Patrick Mannion. ArXiv. 2021. [pdf]

A Practical Guide to Multi-Objective Reinforcement Learning and Planning. Conor F. Hayes, Roxana Rădulescu, 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 Ramos, Marcello Restelli, Peter Vamplew and Diederik M. Roijers. ArXiv. 2021. [pdf]

Master’s Thesis

Dynamic Economic Emissions Dispatch with Thresholded Lexicographic Ordering. Conor F. Hayes. Master’s Thesis in Computer Science. National University of Ireland Galway. 2019. [pdf]