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We study a ubiquitous learning challenge in online principal-agent problems during which the principal learns the agent's private information from the agent's revealed preferences in historical interactions.
Marktform und gleichgewicht
Stackelberg, H. v. 1934 · 1934
Earlier work this paper cites.
Elicitation of personal probabilities and expectations
Savage, L. J. 1971 · 1971
Earlier work this paper cites.
Optimal coordination mechanisms in generalized principal–agent problems
Myerson, R. B. 1982 · 1982
Earlier work this paper cites.
The theory of contracts
Hart, O. D.; and Holmstrm, B. 1986 · 1986
Earlier work this paper cites.
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Earlier work this paper cites.
Leadership with commitment to mixed strategies
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Earlier work this paper cites.
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