TY - GEN

T1 - ROBUST INCENTIVE POLICIES FOR STOCHASTIC DECISION PROBLEMS IN THE PRESENCE OF PARAMETRIC UNCERTAINTY.

AU - Basar, T.

AU - Cansever, D. H.

PY - 1985

Y1 - 1985

N2 - In this paper the authors consider a general class of stochastic incentive decision problems in which the leader has access to the control value of the follower and to private as well as common information on the unknown state of nature. The follower's cost function depends on a finite number of parameters whose values are not known accurately by the leader, and in spite of this parametric uncertainty the leader seeks a policy which would induce the desired behavior on the follower. They obtain such robust policies for the leader, which are smooth, induce the desired behavior at the nominal values of these parameters, and furthermore make the follower's optimal reaction either minimally sensitive or totally insensitive to variations in the values of these parameters from the nominals. The general solution is determined by some orthogonality relations in some appropriately constructed (probability) measure spaces, and leads to particularly simple incentive policies.

AB - In this paper the authors consider a general class of stochastic incentive decision problems in which the leader has access to the control value of the follower and to private as well as common information on the unknown state of nature. The follower's cost function depends on a finite number of parameters whose values are not known accurately by the leader, and in spite of this parametric uncertainty the leader seeks a policy which would induce the desired behavior on the follower. They obtain such robust policies for the leader, which are smooth, induce the desired behavior at the nominal values of these parameters, and furthermore make the follower's optimal reaction either minimally sensitive or totally insensitive to variations in the values of these parameters from the nominals. The general solution is determined by some orthogonality relations in some appropriately constructed (probability) measure spaces, and leads to particularly simple incentive policies.

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M3 - Conference contribution

AN - SCOPUS:0021900047

SN - 0080316697

T3 - IFAC Proceedings Series

SP - 1389

EP - 1393

BT - IFAC Proceedings Series

PB - r IFAC by Pergamon Press

ER -