Improving game bot behaviours through timed emotional intelligence
The video game industry is a very active economic sector focusing on the design and development of entertainment applications. In this sector, different enterprises compete to design innovative video games that exploit physical and emotional capabilities of video gamers in order to achieve high levels of realism. From this point of view, video games research should be enhanced by introducing: (1) novel methodologies for modeling emotions that depict the behaviour of different characters populating a virtual environment, and (2) some abstraction technologies useful to move this emotional intelligence on different game platforms without additional efforts. In this paper, innovative computational intelligence techniques, like the Timed Automata based Fuzzy Controllers, have been hybridized with emotional representation methodologies in order to provide game bots with human-like capabilities and, as a consequence, improve the realism of game under design. In order to allow different competitors to exploit our emotional engine on different hardware platforms, the Fuzzy Markup Language (FML) has been chosen to be the main technology for designing and implementing the bots behaviour. As shown in a case study based on Unreal Tournament 2004, the game bots exploiting our approach provide a more human-likeness behaviour if compared with simple finite state automaton based bots.
games emotions computational intelligence timed automata fuzzy control fuzzy markup language