We study a setting where a principal needs to motivate a team of agents whose combination of hidden efforts stochastically determines an outcome. In a companion paper we devise and study a basic "combinatorial agency" model for this setting, where the principal is restricted to inducing a pure Nash equilibrium. Here, we show that the principal may possibly gain from inducing a mixed equilibrium, but this gain can be bounded for various families of technologies (in particular if a technology has symmetric combinatorial structure). In addition, we present a sufficient condition under which mixed strategies yield no gain to the principal. © 2006 Springer-Verlag.
CITATION STYLE
Babaioff, M., Feldman, M., & Nisan, N. (2006). Mixed strategies in combinatorial agency: (Extended abstract). In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4286 LNCS, pp. 353–364). https://doi.org/10.1007/11944874_32
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