Algorithmic mechanism design (extended abstract)
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Hidden-action in multi-hop routing
Proceedings of the 6th ACM conference on Electronic commerce
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
Policy teaching through reward function learning
Proceedings of the 10th ACM conference on Electronic commerce
Combinatorial agency with audits
GameNets'09 Proceedings of the First ICST international conference on Game Theory for Networks
Free-Riding and Free-Labor in Combinatorial Agency
SAGT '09 Proceedings of the 2nd International Symposium on Algorithmic Game Theory
Computing Optimal Contracts in Series-Parallel Heterogeneous Combinatorial Agencies
WINE '09 Proceedings of the 5th International Workshop on Internet and Network Economics
Optimal Incentives for Participation with Type-Dependent Externalities
WINE '09 Proceedings of the 5th International Workshop on Internet and Network Economics
Combinatorial agency of threshold functions
SAGT'11 Proceedings of the 4th international conference on Algorithmic game theory
Computing optimal contracts in combinatorial agencies
Theoretical Computer Science
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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.