  To recognize an object in an image, the user must apply a combination of
operators, where each operator has a set of parameters. These parameters must
be well adjusted in order to reach good results. Usually, this adjustment is
made manually by the user. In this paper we propose a new method to automate
the process of parameter adjustment for an object recognition task. Our method
is based on reinforcement learning, we use two types of agents: User Agent that
gives the necessary information and Parameter Agent that adjusts the parameters
of each operator. Due to the nature of reinforcement learning the results do
not depend only on the system characteristics but also on the user favorite
choices.
