Ontology-Based Learning for Negotiation

Successful negotiation depends on understanding and responding to participants' needs. Many negotiation approaches assume identical needs and do not take into account other preferences of the participants. However, preferences play a crucial role in the outcome of negotiations. Accordingly, we propose a learning algorithm that can be used by a producer during negotiation to understand consumer's needs and to offer services that respect these preferences. Our proposed algorithm is based on inductive learning but also incorporates the idea of revision. Thus, as the negotiation proceeds, a producer can revise its idea of the customer's preferences. The learning is enhanced with the use of ontologies so that similar service requests can be identified and treated similarly. Further, the algorithm is targeted to learning both conjunctive as well as disjunctive preferences. Hence, even if the consumer's preferences are specified in complex ways, such as conditional rules, our algorithm can learn and guide the producer to create well-targeted offers.