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Stackelberg strategies and incentives in multiperson deterministic decision problems

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3 Author(s)
Ying-Ping Zheng ; Coordinated Sci. Lab., Univ. of Illinois, Urbana, IL, USA ; Tamer Basar ; Jose B. Cruz

Discrete and continuous-time two-person decision problems with a hierarchical decision structure are studied, and the applicability and appropriateness of a function-space approach in the derivation of causal real-time implementable optimal Stackelberg (incentive) strategies under various information patterns are discussed. Results on existence and derivation of incentive strategies for dynamic games formulated in abstract inner-product spaces, in the absence of any causality restriction on the leader's policies, are presented; these results are extended and specialized in two major directions: (1) discrete-time dynamic games, and (2) derivation of causal, physically realizable optimum affine Stackelberg policies for both discrete and continuous-time problems.

Published in:

IEEE Transactions on Systems, Man, and Cybernetics  (Volume:SMC-14 ,  Issue: 1 )