  We investigate systematically the impact of human intervention in the
training of computer players in a strategy board game. In that game, computer
players utilise reinforcement learning with neural networks for evolving their
playing strategies and demonstrate a slow learning speed. Human intervention
can significantly enhance learning performance, but carry-ing it out
systematically seems to be more of a problem of an integrated game development
environment as opposed to automatic evolutionary learning.
