“The Intelligent, the Artificial, and the Random”

Artificial Intelligence (AI) has become a prominent and growing research field in the last couple of years. The aim of AI is to create autonomous computer systems that are able to make rational decisions given the limited amount of resources. Most attention goes nowadays to the AI subdiscipline of Machine Learning, which allows systems to learn on their own by recognizing patterns in large datasets and making decisions based on similar situations. However, another important component of AI is the subdiscipline of Machine Reasoning, which involves algorithms to search efficiently in general solution spaces. Machine Reasoning is essential to AI as responsible decision-making requires considering the consequences of decisions into the future.

The lecture will focus on the reasoning paradigm Monte-Carlo Tree Search (MCTS). In the last fifteen years, MCTS has achieved noticeable success in a wide range of domains, initially in (board) games, but later on in many real-life applications in the field of optimization and scheduling. The random element has been key to its success. The lecture will highlight in which way Maastricht University has contributed to advance the state of the art in this respect, and how this method connects with new developments in the field of AI.