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Title: Information-based incentivisation when rewards are inadequate.
Authors: Taweel, Adel
Keywords: Artificial intelligence - Educational applications
Issue Date: 2014
Abstract: In many cases, intermediaries play a major role in linking between service providers and their target users. Yet, attracting intermediaries at a marketplace to promote a service to their existing customers can be very challenging, since they are usually very busy and would incur additional cost as a result of such promotion. In response, this paper presents an information-based incentivisation framework, which combines financial rewards with other motivating information, in order to incentivise intermediaries at a marketplace to undertake service promotion. Specifically, the intermediaries are associated with a group of incentivising agents, capable of learning the individual motivational needs of these intermediaries, and accordingly target them with the most effective incentives. The incentivising agents collaborate with each other to gather motivational information, by sharing their observations on intermediaries. The proposed incentivisation approach is evaluated through a corresponding agent-based simulation, and the experimental results obtained demonstrate its effectiveness
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