A Truthful Two-Stage Mechanism for Eliciting Probabilistic Estimates with Unknown Costs

This paper reports on the design of a novel two-stage mechanism, based on strictly proper scoring rules, that motivates selfish rational agents to make a costly probabilistic estimate or forecast of a specified precision and report it truthfully to a centre. Our mechanism is applied in a setting where the centre is faced with multiple agents, and has no knowledge about their costs. Thus, in the first stage of the mechanism, the centre uses a reverse second price auction to allocate the estimation task to the agent who reveals the lowest cost. While, in the second stage, the centre issues a payment based on a strictly proper scoring rule. When taken together, the two stages motivate agents to reveal their true costs, and then to truthfully reveal their estimate. We prove that this mechanism is incentive compatible and individually rational, and then present empirical results comparing the performance of the well known quadratic, spherical and logarithmic scoring rules. We show that the ...

• Type: Conference
• Year: 2008
• Where: ECAI
• Authors: Athanasios Papakonstantinou, Alex Rogers, Enrico H. Gerding, Nicholas R. Jennings
• Keywords: Artificial Intelligence, ECAI 2008, Proper Scoring Rule, Scoring Rules, Strictly Proper