The application of stochastic automata to the parameter self-optimization problem is considered theoretically. It is shown that the learning behaviours of stochastic automata in this problem can be reduced to the learning behaviours of stochastic automata under the non-stationary random environments R(Cl(t,ω ), ⃛, C(tr, ω)) which were considered in Baba and Sawaragi (1975).