Title

Usability And Scalability In Human Behavior Models Created By Machine Learning Algorithms

Keywords

Context-based reasoning; Genetic programming; Human bebavior modeling; No free lunch theorem

Abstract

This paper presents initial results of modeling human behavior with a novel algorithm that creates human behavior models automatically by observing human performance. However, these results together with conclusions from the No Free Lunch Theorems signify the scalability of the modeling algorithm. The implication from the No Free Lunch Theorems also indicates how applicable or scalable a machine learning algorithm might be, applied to a new real world problem. Furthermore, the results are universal and might be applicable to many related areas of automatic modeling.

Publication Date

10-1-2006

Publication Title

WSEAS Transactions on Systems

Volume

5

Issue

10

Number of Pages

2434-2441

Document Type

Article

Personal Identifier

scopus

Socpus ID

33746898983 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/33746898983

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