Modelling Human-like Behavior through Reward-based Approach in a First-Person Shooter Game

Ilya Makarov, Peter Zyuzin, Pavel Polyakov, Mikhail Tokmakov, Olga Gerasimova, Ivan Guschenko-Cheverda and Maxim Uriev

MPRA Paper from University Library of Munich, Germany

Abstract: We present two examples of how human-like behavior can be implemented in a model of computer player to improve its characteristics and decision-making patterns in video game. At first, we describe a reinforcement learning model, which helps to choose the best weapon depending on reward values obtained from shooting combat situations.Secondly, we consider an obstacle avoiding path planning adapted to the tactical visibility measure. We describe an implementation of a smoothing path model, which allows the use of penalties (negative rewards) for walking through \bad" tactical positions. We also study algorithms of path nding such as improved I-ARA* search algorithm for dynamic graph by copying human discrete decision-making model of reconsidering goals similar to Page-Rank algorithm. All the approaches demonstrate how human behavior can be modeled in applications with significant perception of intellectual agent actions.

Keywords: Human-like Behavior; Game Arti cial Intelligence; Reinforcement Learning; Path Planning; Graph-based Search; Video Game (search for similar items in EconPapers)
JEL-codes: C57 C91 (search for similar items in EconPapers)
Date: 2016-07-18
New Economics Papers: this item is included in nep-cbe
References: View complete reference list from CitEc
Citations:

Published in CEUR Workshop Proceeding Experimental Economics and Machine Learning.1627(2016): pp. 24-33

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/82878/1/paper2.pdf original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:82878

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().