Approximate implementation in Markovian environments

This paper considers dynamic implementation problems in environments with changing private information (according to Markov processes). A social choice function is approximately implementable if it is correctly implemented an arbitrary large number of times with arbitrary high probability in all (communication) equilibria. We show that if a social choice function is strictly efficient in the set of social choice functions that satisfy an undetectability condition, then it is approximately implementable.