Given a state, a most straightforward policy is to select the action that corresponds to the maximum mean Q-value estimated by the GP.
since the objective is to learn the Q-function associated with the optimal policy by interacting directly with users, the policy must exhibit some form of stochastic behaviour in order to explore alternatives during the process of learning.