Testing learning strategies

In this paper we present an experiment designed to test whether an automatic system can learn a set of rules in a similar way as human beings learn the same set of rules. In order to do that, we have conducted two experiments. The first of them has been done with a group of seventy people, while the second one has been done by running an automatic learning system designed by ourselves. The paper contains the results of both tests, and a comparison of the learning curves of both types of subjects: humans and automatic agents. We also analyze the differences and similarities by considering how humans and agents construct their knowledge about the rules. By using both types of analysis, we study how close is the learning process of our automatic agents to obtaining a success in a Turing test.