The reusability of learning material is a very important feature to design learning environments for real-life learning. The reusability of learning material is based on three main features: modularity, discoverability, and interoperability. The object learning approach aims to provide these features. At the same time, several researchers on intelligent learning environments have proposed the use of artificial intelligence through architectures based on agent societies. Teaching systems based on multiagent architectures make it possible to support the development of more interactive and adaptable systems. We proposed an approach where learning objects are built based on agent architectures: the intelligent learning object (ILO). This chapter addresses the improvement of interoperability among learning objects in agent-based learning environments by integrating learning objects technology and the multiagent systems approach. It presents the ILO agent’s basic architecture and a case study.