  Although the Music Sight Reading process has been studied from the cognitive
psychology view points, but the computational learning methods like the
Reinforcement Learning have not yet been used to modeling of such processes. In
this paper, with regards to essential properties of our specific problem, we
consider the value function concept and will indicate that the optimum policy
can be obtained by the method we offer without to be getting involved with
computing of the complex value functions. Also, we will offer a normative
behavioral model for the interaction of the agent with the musical pitch
environment and by using a slightly different version of Partially observable
Markov decision processes we will show that our method helps for faster
learning of state-action pairs in our implemented agents.
