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Incongruity Theory Applied in Dynamic Adaptive Game Artificial Intelligence

Authors: Kevin N. Francisco; Johann Paulo L. Ruste; Ria A. Sagum; Yun Seop Song; Darl Sander G. Sy;

Incongruity Theory Applied in Dynamic Adaptive Game Artificial Intelligence

Abstract

The Theory of Incongruity is a theory in psychology that states that people create mental concepts about the world in two forms/concepts such as the context and system complexity. The researchers presents an adaptive A.I in which it interacts with a real person and incorporates the theory in order to monitor how the user feels while playing or interacting with the A.I. Two algorithms will be utilized in order to achieve the desired adaptability of the A.I. namely, dynamic scripting and case base reasoning. The goal of the study is to create an A.I. that will be able to react fast and adapt to real human players based on how they feel or what they think regarding the decisions made by the A.I. This study aims to give a player a more thrilling and exciting experience thus, improving the quality of entertainment games provide. The study also focuses on pulling the gamer up the scale in order to improve his skills in game. Giving the player a chance to win by scaling his current skill level but still targeting in the end to win makes the adaptive A.I. more fun to interact with and prove to give a positive reaction or experience to the gamer.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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