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For each stationary policy, the associated Markov chain {X n } in the perturbed model is aperiodic It is not dif cult to verify that for each stationary policy the average cost per time unit in the perturbed model is the same as that in the original model For the unichain case this is an immediate consequence of the representation (627) for the average cost and the fact that for each stationary policy the Markov chain {X n } has the same equilibrium probabilities as the Markov chain {Xn } in the original model For the multichain case, a similar argument can be used to show that the wo models are in fact equivalent Thus the value-iteration algorithm can be applied to the perturbed model in order to solve the original model In speci c problems involving periodicities, the optimal value of is usually not clear beforehand; empirical investigations indicate that = 1 is usually a satisfactory choice 2 Modi ed value iteration with a dynamic relaxation factor Value iteration does not have the fast convergence of policy iteration The number of iterations required by the value-iteration algorithm is problem dependent and increases when the number of problem states gets larger Also, the tolerance number in the stopping criterion affects the number of iterations required The stopping criterion should be based on the lower and upper bounds mn and Mn but not on any repetitive behaviour of the generated policies R(n) The convergence rate of value iteration can often be accelerated by using a relaxation factor, such as in successive overrelaxation for solving a single system of linear equations Then at the nth iteration a new approximation to the value function Vn (i) is obtained by using both the previous values Vn 1 (i) and the residuals Vn (i) Vn 1 (i) It is possible to select dynamically a relaxation factor and thus avoid the experimental determination of the best value of a xed relaxation factor The following modi cation of the standard value-iteration algorithm can be formulated Steps 0, 1, 2 and 3 are as before, while step 4 of the standard value-iteration algorithm is modi ed as follows Step 4(a) Determine the states u and v such that Vn (u) Vn 1 (u) = mn and compute the relaxation factor = Mn mn + Mn mn , j I {puj (Ru ) pvj (Rv )}{Vn (j ) Vn 1 (j )} and Vn (v) Vn 1 (v) = Mn. 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