Providing a Recommended Trading Agent to a Population: A Novel Approach

This paper presents a novel approach for providing automated trading agents to a population, focusing on bilateral negotiation with unenforceable agreements. A new type of agents, called semicooperative (SC) agents is proposed for this environment. When these agents negotiate with each other they reach a pareto-optimal solution that is mutually beneficial. Through extensive experiments we demonstrate the superiority of providing such agents for humans over supplying equilibrium agents or letting people design their own agents. These results are based on our observation that most people do not modify SC agents even though they are not in equilibrium. Our findings introduce a new factor —human response to provided agents — that should be taken into consideration when developing agents that are provided to a population.