Two Human-Like Imitation-Learning Bots with Probabilistic Behaviors

We present details of two imitation-learning, game-playing agents – "SVMBot" and "PETBot" – that feature probabilistic modelling of some low-level combat behaviours. Both bots used a support-vector-machine approach for aiming and a novel, probabilistic model for jumping behaviours. PET-Bot also used a probability-estimation-tree (PET) technique for combat movement. The bots were developed for the FPS game Unreal Tournament 2004 and one of each was submitted to the qualification round (SVMBot) and the final round (PETBot) of the 2009 2K BotPrize competition where they obtained good results. They were then compared with each other as independent variables in a human-computer-interaction (HCI) between-subjects experiment.

[1]  Cédric Buche,et al.  Analysis of the Protocols Used to Assess Virtual Players in Multi-player Computer Games , 2017, IWANN.

[2]  Abdennour El Rhalibi,et al.  Machine learning techniques for FPS in Q3 , 2004, ACE '04.

[3]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[4]  Daniel M. Johnson,et al.  Creating engaging artificial characters for games , 2003, ICEC.

[5]  David M. Magerman.  Statistical Decision-Tree Models for Parsing , 1995, ACL.

[6]  Benjamin Geisler,et al.  An Empirical Study of Machine Learning Algorithms Applied to Modeling Player Behavior in a "First Person Shooter" Video Game , 2002 .

[7]  Janet Mancini Billson,et al.  Focus Groups: A Practical Guide for Applied Research , 1989 .

[8]  øöö Blockinøø.  Well-Trained PETs : Improving Probability Estimation , 2000 .

[9]  Rudolf Kadlec,et al.  Towards Fast Prototyping of IVAs Behavior: Pogamut 2 , 2007, IVA.

[10]  Mihai Polceanu,et al.  MirrorBot: Using human-inspired mirroring behavior to pass a turing test , 2013, 2013 IEEE Conference on Computational Inteligence in Games (CIG).

[11]  David Gamez,et al.  A Neurally Controlled Computer Game Avatar With Humanlike Behavior , 2013, IEEE Transactions on Computational Intelligence and AI in Games.

[12]  J. Ross Quinlan,et al.  Induction of Decision Trees , 1986, Machine Learning.

[13]  J. Ross Quinlan,et al.  C4.5: Programs for Machine Learning , 1992 .

[14]  Philip Hingston,et al.  A Turing Test for Computer Game Bots , 2009, IEEE Transactions on Computational Intelligence and AI in Games.

[15]  Philip Hingston,et al.  A new design for a Turing Test for Bots , 2010, Proceedings of the 2010 IEEE Conference on Computational Intelligence and Games.

[16]  Radford M. Neal.  Pattern Recognition and Machine Learning , 2007, Technometrics.

[17]  Cédric Buche,et al.  Bot Believability Assessment: A Novel Protocol & Analysis of Judge Expertise , 2018, 2018 International Conference on Cyberworlds (CW).

[18]  Bernard Gorman.  IMITATIVE LEARNING OF COMBAT BEHAVIOURS IN FIRST-PERSON COMPUTER GAMES , 2007 .

[19]  Christian Bauckhage,et al.  Towards a Fair 'n Square Aimbot - Using Mixtures of Experts to Learn Context Aware Weapon Handling , 2004 .

[20]  Rudolf Kadlec,et al.  Pogamut 3 Can Assist Developers in Building AI (Not Only) for Their Videogame Agents , 2009, AGS.

[21]  Wray L. Buntine,et al.  Learning classification trees , 1992 .