  We study the possibility to employ neural networks to simulate jet clustering
procedures in high energy hadron-hadron collisions. We concentrate our analysis
on the Fermilab Tevatron energy and on the $k_\bot$ algorithm. We consider both
supervised multilayer feed-forward network trained by the backpropagation
algorithm and unsupervised learning, where the neural network autonomously
organizes the events in clusters.
