Multi-agent negotiation and price discrimination for information goods

We have developed a mechanism that supports trading database tuples in a multi-agent system. The mechanism enables negotiation and evaluation of database-based information goods. We propose various policies for dynamic pricing of information goods. We have developed a test-bed that simulates a multi-agent system where each agent uses the offered mechanism and have evaluated the system performance when sellers use different pricing policies in two market environments, namely competitive and non-competitive. The investigated pricing policies include two novel pricing policies that implement negotiation and price discrimination across consumers. These are compared to two policies known in the art, which implement dynamic posted pricing. We have empirically demonstrated the superiority of the offered policies in maximizing sellers' gains. We have additionally identified equilibria profiles of these policies.