International audience In this paper we propose a neural network allowing a mobile robot to learn artwork appreciation. The learning is based on the social referencing approach. The robot acquires its knowledge (artificial taste) from the interaction with humans. We present and analyze specifically the visual system, its impact on the robot behavior, and at the end, we analyze the readability of our robot behavior according to visitors comments. We show that the low level spatial competition between the values associated to areas of interest in the image are important for the coherence of the robot's object evaluation and the readability of its behavior. Index Terms— Artificial intelligence, neural networks, Human robot interactions, computer vision.