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 on-line 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 1 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.