Multi-agent Negotiation to Support an Economy for Online Help and Tutoring

We have designed a computational architecture for a "learning economy" based on personal software agents who represent users in a virtual society and assist them in finding learning resources and peer help. In order to motivate users to participate, to share their experience, offer help and create online learning resources, payment is involved in virtual currency and the agents negotiate for services and prices, as in a free market. We model negotiation among personal agents by means of an influence diagram, a decision theoretic tool. In addition, agents create models of their opponents during negotiation to predict opponent actions. Simulations and an experiment have been carried out to test the effectiveness of the negotiation mechanism and learning economy.