In virtual worlds, character credibility suffers from an increasing discrepancy between visual realism, physical modelling quality and behaviour simulation weakness. As behaviour credibility is firmly embedded in the eye of the human observer, it needs to be as close to human expectation as possible. In this study, we define a learning process able to build rule-based behaviour from the observation of a human tutor controlling a virtual agent and from a progressive fusion of rules. The ability of this imitation process to model human-controlled behaviour is assessed upon experiments carried out on a flee-attack scenario for an RTS game. Its efficiency is examined in a game development context.