  In this article, we present a new machine learning model by imitation based
on the linguistic description of complex phenomena. The idea consists of,
first, capturing the behaviour of human players by creating a computational
perception network based on the execution traces of the games and, second,
representing it using fuzzy logic (linguistic variables and if-then rules).
From this knowledge, a set of data (dataset) is automatically created to
generate a learning model based on decision trees. This model will be used
later to automatically control the movements of a bot. The result is an
artificial agent that mimics the human player. We have implemented, tested and
evaluated this technology. The results obtained are interesting and promising,
showing that this method can be a good alternative to design and implement the
behaviour of intelligent agents in video game development.
