5 papers
Predicting Long-Term Self-Rated Health in Small Areas Using Ordinal Regression and Microsimulation
Seán Caulfield Curley, Karl Mason, Patrick Mannion
This paper presents an approach for predicting the self-rated health of individuals in a future population utilising the individuals' socio-economic characteristics. An open-source…
Ireland in 2057: Projections using a Geographically Diverse Dynamic Microsimulation
Seán Caulfield Curley, Karl Mason, Patrick Mannion
This paper presents a dynamic microsimulation model developed for Ireland, designed to simulate key demographic processes and individual life-course transitions from 2022 to 2057.…
Demonstration-Guided Continual Reinforcement Learning in Dynamic Environments
Xue Yang, Michael Schukat, Junlin Lu +3
Reinforcement learning (RL) excels in various applications but struggles in dynamic environments where the underlying Markov decision process evolves. Continual reinforcement learn…
MOMA-AC: A preference-driven actor-critic framework for continuous multi-objective multi-agent reinforcement learning
Adam Callaghan, Karl Mason, Patrick Mannion
This paper addresses a critical gap in Multi-Objective Multi-Agent Reinforcement Learning (MOMARL) by introducing the first dedicated inner-loop actor-critic framework for continuo…
Inferring Preferences from Demonstrations in Multi-objective Reinforcement Learning
Junlin Lu, Patrick Mannion, Karl Mason
Many decision-making problems feature multiple objectives where it is not always possible to know the preferences of a human or agent decision-maker for different objectives. Howev…