Conference articles PUBLISHED

1. Oesterheld, C; Conitzer, V, Minimum-Regret Contracts for Principal-Expert Problems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12495 LNCS (January, 2020), pp. 430-443 [doi].
   (last updated on 2024/04/24)

   Abstract:
   We consider a principal-expert problem in which a principal contracts one or more experts to acquire and report decision-relevant information. The principal never finds out what information is available to which expert, at what costs that information is available, or what costs the experts actually end up paying. This makes it challenging for the principal to compensate the experts in a way that incentivizes acquisition of relevant information without overpaying. We determine the payment scheme that minimizes the principal’s worst-case regret relative to the first-best solution. In particular, we show that under two different assumptions about the experts’ available information, the optimal payment scheme is a set of linear contracts.