They Know: A Pathfinding Rational Agent via Knowledge Acquistion Modeling from Player Behavior and Enhanced A* Algorithm


Authors
  • Joshua Rei Aviles
  • Joshua Philip Barcena
  • Christopher John Hispano
  • Jaen Dave Lucas
  • Edwin M. Torralba
  • University of Santo Tomas
Published in


Abstract
  • Modern games have used Artificial Intelligence as a core element of game design and mechanics. Artificial Intelligence has thrived in many fields; however, the enhancement of pathfinding algorithms of AIs in games have remained stagnant. Moreover, numerous issues with regards to the exploitable plot of games have been raised by several gamers and game developers. The purpose of this research is to develop They Know - a survival themed thriller game with 4J MT-Adaptive A* - an adaptive and enhanced pathfinding algorithm created using A* as basis, to reduce the predictability of in-game agents by using the developed algorithm and by modifying agents with knowledge acquisition, to distinguish the personality and emotion of modern players based on the reaction of players to in-game situations, and to acquire data for determining the motivation of contemporary gamers for playing. The efficiency of the developed algorithm was compared with Lazy MT – Adaptive A* developed by Koenig (2007). Questionnaires developed by HEXACO, Power (2017), and Demetrovics (2011) were used as standards for acquiring data from the respondents to determine the respondents’ personality, degree of predictability of the game, and the motivation of players in playing. Data were gathered from grades 11 and 12 students of the University of Santo Tomas – Senior High School.


Keywords
  • 4J MT-Adaptive A*, Lazy MT-Adaptive A*, Knowledge Acquisition, Adaptive, Predictability




Cite As
  • APA 7th Edition:
    Aviles, J., Barcena, J., Hispano, C., Lucas, J., & Torralba, E. (2019). They Know: A Pathfinding Rational Agent via Knowledge Acquistion Modeling from Player Behavior and Enhanced A* Algorithm. Innovatus, 2(1), 6-11.
  • Harvard:
    Aviles, J., Barcena, J., Hispano, C., Lucas, J. and Torralba, E., 2019. They Know: A Pathfinding Rational Agent via Knowledge Acquistion Modeling from Player Behavior and Enhanced A* Algorithm. Innovatus, 2(1), pp.6-11.
  • IEEE:
    [1] J. Aviles, J. Barcena, C. Hispano, J. Lucas and E. Torralba, "They Know: A Pathfinding Rational Agent via Knowledge Acquistion Modeling from Player Behavior and Enhanced A* Algorithm", Innovatus, vol. 2, no. 1, pp. 6-11, 2019.


References
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  • Koenig, S., Likhachev, M., & Sun, X. (2007). Speeding up moving-target search. Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems - AAMAS 07. doi:10.1145/1329125.1329353
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