Predicting opponent resource allocations when qualitative and contextual information is not available

Baylor Wetzel, Steve Jensen, Maria L Gini

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

How one predicts another's behavior depends on the type of behavior being predicted and the context of the prediction. In this paper we describe an agent based on ELPH [1] for a two player, zero-sum game where success depends on predicting the opponent's resource allocation in a domain lacking qualitative and contextual information. This problem is made difficult in that many of the traits necessary for many opponent modeling algorithms do not exist (there is no meaningful context, all options are of equal value, there are no meaningful sequences, no signaling of intention, etc.), the agent's behavior changes significantly and frequently and the agent is actively trying to be unpredictable.

Original languageEnglish (US)
Title of host publicationFDG 2009 - 4th International Conference on the Foundations of Digital Games, Proceedings
Pages333-334
Number of pages2
DOIs
StatePublished - Dec 1 2009
Event4th International Conference on the Foundations of Digital Games, ICFDG 2009 - Orlando, FL, United States
Duration: Apr 26 2009Apr 30 2009

Publication series

NameFDG 2009 - 4th International Conference on the Foundations of Digital Games, Proceedings

Other

Other4th International Conference on the Foundations of Digital Games, ICFDG 2009
CountryUnited States
CityOrlando, FL
Period4/26/094/30/09

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