為因應人類生理或心理上的需求，而產生了形形色色之服務。隨著高科技不斷地發展，人類的未來生活，將會是充滿e化服務的生活環境。在此環境中，並非所有人均能了解各應用服務，更不知該選擇何服務才能滿足自身之多重需求。本研究擬設計一決策機制，當人們有多重需求時，能考慮有形及無形資源之有效利用，並考量不同個體之使用偏好及興趣，提供適合個人的e化服務建議。本研究之應用環境，符合垃圾桶模式中的無政府狀態之三大特性，然而原垃圾桶決策方式卻不適用於個人。因此，本研究之主體，為一智慧代理人，將以垃圾桶模式的決策原理做為基礎，並對其加以修改，分為二階段的決策過程。在第一階段，將使用一考量資源使用效率之task-chosen演算法，並搭配增強式學習中之AH-learning演算法；在第二階段，則是使用BDI代理人的架構。本研究所提出之提供e化服務建議的決策機制，預期將促使應用服務能不斷地創新及進步，並使資源獲得更有效之利用，使得人類擁有高品質的生活環境。 / There are manifold services, in order to fulfill people’s physical and mental needs. Through the continuous development of high technique, people will live in the environment surrounding e-services in the future. In this environment, it is hart for everyone to understand all e-services and choose a service to fulfill selves multiple needs. Therefore, the paper presents a decision mechanism which providing suitable e-service suggestion for everyone when they have multiple needs, considering the using utility of resources include tangible and intangible, and different preferences and interests for different people. This paper’s applying environment satisfies the three general properties of organized anarchies of “Garbage Can Model”. However, the decision method in garbage can model is not suitable to individual. The most important part of the paper is an intelligent agent, based on garbage can model theory but modify it appropriately. This intelligent agent uses two phase decision process. First phase, use a task-chosen algorism considering resource utility and AH-learning in reinforcement learning. Second phase, use the architecture of BDI agent. This paper presents a decision strategy providing e-service suggestion, and expects to promote innovative application services and use resource effectively. Finally, all people will enjoy high quality life.