  With the growing number of textual resources available, the ability to
understand them becomes critical. An essential first step in understanding
these sources is the ability to identify the part of speech in each sentence.
Arabic is a morphologically rich language, wich presents a challenge for part
of speech tagging. In this paper, our goal is to propose, improve and implement
a part of speech tagger based on a genetic alorithm. The accuracy obtained with
this method is comparable to that of other probabilistic approaches.
