過去多重代理人系統相關研究中，皆假設任務是預先知道而且確定的，這使得它們無法即時滿足使用者需求，因而在實務上受到限制。因此本研究期望能將多重代理人系統的工作向前延伸，引入人類社會中的價值觀，進而模擬出人類解決問題的思考模式，將能夠放寬任務給定的限制，幫助傳統多重代理人系統提昇彈性、適用於更為動態複雜的環境，即時地滿足使用者需求。任務發掘意指幫助多重代理人系統找出合適任務的過程，將任務發掘應用於多重代理人系統，最主要的挑戰在於－「什麼任務才能滿足需求」；換句話說，「找出需求」。價值(value)正是引起社會交換(social exchange)的元素，價值觀則是人類對於該價值之看法。重視該價值觀為希望於交換過程中獲得該價值，不重視該價值觀為願意於交換過程中犠牲該價值，然而重視有程度之分，即希望獲得/願意犠牲之優先順序。衝突即為依據該優先順序以重視之價值換取不重視之價值的交換行為；最低衝突則為以最不重視之價值換取最重視之價值的交換行為。若能以最低衝突進行交換即最能符合使用者價值觀；最符合使用者價值觀之決策則能滿足使用者之需求。透過本研究所發展之衝突解析演算法，將能夠找出與使用者價值觀最低衝突之代理人團隊，以使用者價值觀點出發，發掘出情境化任務，有效地滿足使用者需求。 / Most existing multi-agent systems (MAS) presume that the tasks to be resolved are given. However, this assumption sometimes renders the systems unrealistic. A sound mission discovery mechanism would exempt this assumption and offer flexibility and adaptation in resolving the user’s problem in dynamic complexity environments. The major challenge of mission discovery in MAS, in general, rests on how to associate missions to the user’s needs (i.e., the identification of the user’s needs). “Value” is anything that can give rise to exchange. For instance, if someone can help his friend no matter what the price he would pay for, then it means that the moral value surpasses the economics value for the case. Based on the theory of social exchange, this paper devises a Conflict Resolution Algorithm that aims to allocate an agent team of the members with the least value conflict so as to discover the contextualized missions that could fulfill the user’s needs.