![](/images/graphics-bg.png)
Active Player Modeling in the Iterated Prisoner’s Dilemma
Joint Authors
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2016, Issue 2016 (31 Dec. 2015), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-02-18
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
The iterated prisoner’s dilemma (IPD) is well known within the domain of game theory.
Although it is relatively simple, it can also elucidate important problems related to cooperation and trust.
Generally, players can predict their opponents’ actions when they are able to build a precise model of their behavior based on their game playing experience.
However, it is difficult to make such predictions based on a limited number of games.
The creation of a precise model requires the use of not only an appropriate learning algorithm and framework but also a good dataset.
Active learning approaches have recently been introduced to machine learning communities.
The approach can usually produce informative datasets with relatively little effort.
Therefore, we have proposed an active modeling technique to predict the behavior of IPD players.
The proposed method can model the opponent player’s behavior while taking advantage of interactive game environments.
This experiment used twelve representative types of players as opponents, and an observer used an active modeling algorithm to model these opponents.
This observer actively collected data and modeled the opponent’s behavior online.
Most of our data showed that the observer was able to build, through direct actions, a more accurate model of an opponent’s behavior than when the data were collected through random actions.
American Psychological Association (APA)
Park, HyunSoo& Kim, Kyung-Joong. 2016. Active Player Modeling in the Iterated Prisoner’s Dilemma. Computational Intelligence and Neuroscience،Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1099753
Modern Language Association (MLA)
Park, HyunSoo& Kim, Kyung-Joong. Active Player Modeling in the Iterated Prisoner’s Dilemma. Computational Intelligence and Neuroscience Vol. 2016, no. 2016 (2015), pp.1-13.
https://search.emarefa.net/detail/BIM-1099753
American Medical Association (AMA)
Park, HyunSoo& Kim, Kyung-Joong. Active Player Modeling in the Iterated Prisoner’s Dilemma. Computational Intelligence and Neuroscience. 2016. Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1099753
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1099753