Learning rules of a card game from video

Authors:
Shyamanta M. Hazarika;Alexy Bhowmick
Affiliations:
School of Engineering, Tezpur University, Tezpur, India;School of Engineering, Tezpur University, Tezpur, India
Venue:
Artificial Intelligence Review
Year:
2012

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Abstract

This paper presents a framework for automatically learning rules of a simple game of cards using data from a vision system observing the game being played. Incremental learning of object and protocol models from video, for use by an artificial cognitive agent, is presented. iLearn--a novel algorithm for inducing univariate decision trees for symbolic datasets is introduced. iLearn builds the decision tree in an incremental way allowing automatic learning of rules of the game.