Research direction
GAIHA is the emerging research direction structuring part of my current work at UCLouvain. It focuses on the study and design of artificial intelligence systems that are both general across tasks and, when relevant, human-like in their behaviour and reasoning.
The ambition of GAIHA is to better understand and develop intelligent agents that can operate across diverse situations rather than only in narrow, highly specialised settings. At the same time, this direction is interested in agents whose behaviour can, in some cases, be analysed in relation to human-like decision-making, strategies, and reasoning processes.
In this perspective, games play a central role. They provide rich, controlled, and highly expressive environments in which intelligence, learning, planning, uncertainty, explainability, and interaction can all be studied in a rigorous way.
This makes games not only a research topic in themselves, but also a powerful framework for exploring broader questions in Artificial Intelligence.
Games provide controlled environments for studying complex decision-making.
They make it possible to compare agents across many tasks and settings.
They offer a strong bridge between theoretical AI, human behaviour, and practical experimentation.
Current work connected to GAIHA includes research on general game playing, human-like game-playing agents, imperfect-information environments, learning and decision-making, and computational models of intelligence.
It also extends to broader and interdisciplinary collaborations, including projects related to cultural heritage, computational game studies, and applications connected to domains such as prosthetics and assistive technologies.
In this sense, GAIHA should be understood as a structuring research direction: one that gives coherence to a broad range of projects while remaining open to new collaborations and emerging topics.
Ludii
A general game system for modelling, analysing, and playing a wide range of games.
GameTable COST Action
An interdisciplinary network exploring computational approaches to tabletop games heritage.
WoodStock
A general game player based on stochastic constraint satisfaction.
I am interested in supervising motivated students and discussing internship, master’s, and PhD-level projects related to GAIHA.
Potential topics include game AI, general AI, human-like agents, imperfect-information games, reinforcement learning, explainability, and interdisciplinary AI applications.
If you are interested in these topics, please feel free to get in touch.