Human-like combat behaviour via multiobjective neuroevolution

Abstract

Although evolution has proven to be a powerful search method for discovering effective behaviour for sequential decision-making problems, it seems unlikely that evolving for raw performance could result in behaviour that is distinctly human-like. This chapter demonstrates how human-like behaviour can be evolved by restricting a bot's actions in a way consistent with human limitations and predilections. This approach evolves good behaviour, but assures that it is consistent with how humans behave. The approach is demonstrated in the bot for the commercial first-person shooter videogame Unreal Tournament 2004. 's human-like qualities allowed it to take second place in BotPrize 2010, a competition to develop human-like bots for Unreal Tournament 2004. This chapter analyzes, explains how it achieved its current level of humanness, and discusses insights gained from the competition results that should lead to improved human-like bot performance in future competitions and in videogames in general.