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AN OVERVIEW OF AN AUTONOMOUS INTELLIGENT SYSTEM
WITH AN EMBEDDED MACHINE LEARNING MECHANISM
Ramón García Martínez (1, 2)
1- Buenos Aires Institute of Technology
2.- Intelligent Systems Laboratory. Computer Science Department. School of Engineering. University of Buenos Aires
ABSTRACT
Adress: Bynón 1605. Adrogue (1846). Buenos Aires. ARGENTINA’
e-mail: rgm@mara.fi.uba.ar, rgm@tba.edu.ar
An overview of the archítecture of the system is given, the system sensor sub-system and
the process of building local theories is defined, the planner that the system uses% build
plans that permit to it to reach the self-proposed objectíves ís introduced and the ponderator
that permits to obtaín a measure from how good or how bad is the generated plan ís given,
finallysome results of experimentation are descríbed.
19 INTRODUCTION
Machine Learning [Carbonell et al., 1983; 1986; Kodratoff & Carbonell, 19901 ís a field of
Artifícial Intelligence whích has taken impulse in the last years. Among the díferent types of
Machine Learning techniques, those based on observatíon and discovery are the best
modelízers for the human behavíor.
From this point of view, ít is interestíng to study the ways in which an autonomous system
[Fritz, 1984; Frítz et al., 1989; García Martínez, 19901 can buíld automatically theories whích “
modelices íts enviroment. This theoríes can be used by the system to improve its behavior
in response to changes ín íts envíroment.
Theory formatíon by heuristic mutatíon of observartíons [García Martínez, 1992; 1993a;
1993c) have been proposed as a type of Machine Learning techníque based onobservatíon’
and active experímentation for autonomous íntelligent systems [García, Martínez, 1993b;
1993d].
In this paper is proposed the integrated architecture of a system that with elemental
Wmponents shows an autonomous intelligent behavíor. The presented archítecture iS’
guided to try of solving the machine learning problem of the model of the environment (this
is: what are,the consequences of applyíng determíned actíons to the environment) departing of
no previous knowledge. To accelerate the convergence of the leatned model ís proposed
the utílízation of heurístics and to handle the contradictíons among the generated theories íS
proposed the utilízation of estimators of probabilíty distributíon.
Consideratíons are accomplished on the problem of building theories; the limits of the
problem are defíned; a method of building theoríes based on the application of heuristic of’
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