TY - CHAP
T1 - Information-based Incentivisation when Rewards are Inadequate
AU - Mahmoud, Samhar
AU - Barakat, Lina
AU - Miles, Simon
AU - Taweel, Adel
AU - Delaney, Brendan
AU - Luck, Michael
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84923171870&partnerID=8YFLogxK
U2 - 10.3233/978-1-61499-419-0-591
DO - 10.3233/978-1-61499-419-0-591
M3 - Conference paper
AN - SCOPUS:84923171870
SN - 9781614994183
VL - 263
T3 - Frontiers in Artificial Intelligence and Applications
SP - 591
EP - 596
BT - Frontiers in Artificial Intelligence and Applications
PB - IOS Press
T2 - 21st European Conference on Artificial Intelligence, ECAI 2014
Y2 - 18 August 2014 through 22 August 2014
ER -