Eliciting Informative Feedback: The Peer-Prediction Method
Management Science
Prediction Mechanisms That Do Not Incentivize Undesirable Actions
WINE '09 Proceedings of the 5th International Workshop on Internet and Network Economics
A truth serum for sharing rewards
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 03
AgentSwitch: towards smart energy tariff selection
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Smart pricing scheme: A multi-layered scoring rule application
Expert Systems with Applications: An International Journal
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This paper presents a novel scoring rule-based strictly dominant incentive compatible mechanism that encourages agents to produce costly estimates of future events and report them truthfully to a centre. Whereas prior work has assumed a fixed budget for payment towards agents, this work makes use of prior information held by the centre and assumes a budget that is determined by the savings made through the use of the agents' information over the centre's own prior information. This mechanism is compared to a simple benchmark mechanism wherein the savings are divided equally among all home agents, and a cooperative solution wherein agents act to maximise social welfare. Empirical analysis is performed in which the mechanism is applied to a simulation of the smart grid whereby an aggregator agent must use home agents' information to optimally purchase electricity. It is shown that this mechanism achieves up to 77% of the social welfare achieved by the cooperative solution.