Modelling a Human-Like Bot in a First Person Shooter Game

Antonio Miguel Mora, Francisco Aisa, Pablo García-Sánchez, Pedro Ángel Castillo and Juan Julián Merelo
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Antonio Miguel Mora: University of Granada, Granada, Spain
Francisco Aisa: Rockstar Games, Edinburgh, Scotland, UK
Pablo García-Sánchez: University of Granada, Granada, Spain
Pedro Ángel Castillo: University of Granada, Granada, Spain
Juan Julián Merelo: University of Granada, Granada, Spain

International Journal of Creative Interfaces and Computer Graphics (IJCICG), 2015, vol. 6, issue 1, 21-37

Abstract: Autonomous agents in videogames, usually called bots, have tried to behave as human players from their emergence more than 20 years ago. They normally try to model a part of a human expert player's knowledge with respect to the game, trying to become a competitive opponent or a good partner for other players. This paper presents a deep description of the design of a bot for playing 1 vs. 1 Death Match mode in the first person shooter Unreal Tournament™ 2004 (UT2K4). This bot uses a state-based Artificial Intelligence model which emulates a big part of the behavior/knowledge (actions and tricks) of an expert human player in this mode. This player has participated in international UT2K4 championships. The behavioral engine considers primary and secondary actions, and uses a memory approach. It is based in an auxiliary database for learning about the fighting arena, so it stores weapons and items locations once the bot has discovered them, as a human player would do. This so-called Expert Bot has yielded excellent results, beating the game default bots even in the hardest difficulty, and being a very hard opponent for medium-level human players.

Date: 2015
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International Journal of Creative Interfaces and Computer Graphics (IJCICG) is currently edited by Mehdi Khosrow-Pour

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