Description

In this project, we use techniques like Bayesian Optimization and Intelligent Trial-and-error to adapt content to users and bots.

So far, we have experimented with planning agents and with human players, but we plan to expand this line of work to Reinforcement Learning agents in the context of Curriculum Learning.

Related Research

• Finding Game Levels with the Right Difficulty in a Few Trials through Intelligent Trial-and-Error.
• Fast Game Content Adaptation Through Bayesian-based Player Modelling.