Output details

BLGAN: Bayesian Learning and Genetic Algorithm for Supporting Negotiation With Incomplete Information

<22> This work was published in a top IEEE Journal (acceptance rate:7%). For one-to-one negotiation with complete information, it proved mathematical theorems for determining an agent’s optimal strategy. It is the first to use the synergy between Bayesian learning (BL) and genetic algorithm (GA) to deal with the difficult problem of determining an agent’s optimal strategy in one-to-one negotiation with incomplete information by learning an opponent’s private information. Favorable empirical results validated that agents adopting BL-GA achieved significantly better negotiation outcomes than agents adopting either GA or BL. Other groups (e.g., BeijingUPostTel) used BL-GA for performance comparison.