Decision rules and decision markets

We explore settings where a principal must make a decision about which action to take to achieve a desired outcome. The principal elicits the probability of achieving the outcome by following each action from a self-interested (but decision-agnostic) expert. We prove results about the relation between the principal's decision rule and the scoring rules that determine the expert's payoffs. For the most natural decision rule (where the principal takes the action with highest success probability), we prove that no symmetric scoring rule, nor any of Winkler's asymmetric scoring rules, have desirable incentive properties. We characterize the set of differentiable scoring rules with desirable incentive properties and construct one. We then consider decision markets, where the role of a single expert is replaced by multiple agents that interact by trading with an automated market maker. We prove a surprising impossibility for this setting: an agent can always benefit from exag...

• Type: Conference
• Year: 2010
• Where: ATAL
• Authors: Abraham Othman, Tuomas Sandholm
• Keywords: ATAL 2010, Decision Markets, Decision Rules, Intelligent Agents, Scoring Rules