This paper proposes a model that can learn the meanings of instructions (for example, “good” and “bad”.). This model assumes that an advisee learns the meanings of instructions in parallel with learning the evaluation of its action experience. The reinforcement learning algorithm is adopted for the action learning. We conducted experiments with a robot simulator. The result of the experiments suggests that our model can learn not only evaluation-instructions but also two types of instruction (evaluation-instructions and direction-instructions) simultaneously. This model can be thought as a basic model of an intelligent agent that can learn the meanings of instructions.