Ubiquitous computing features the seamless integration of computer systems into the everyday lives of users to provide information and functionalities anytime and anywhere. Such systems encompass different kinds of sensors and mobile devices interconnected through a combination of several wireless network technologies. A particular trend in this area is exploring the Ambient Intelligence (AmI) paradigm, which aims at the integration of innovative technologies to create computer-mediated environments that support user activities through specific services, with minimal user intervention. In AmI systems, reasoning is fundamental for triggering actions or adaptations according to specific situations that may be meaningful and relevant to some applications. Most middleware systems adopt a centralized approach for their reasoning mechanisms. In AmI environments, however, these reasoning operations may need to evaluate context data collected from distributed sources and stored in different devices, as usually not all context data is readily available to the reasoners within a ubiquitous system. The goal of this thesis is to propose a decentralized reasoning approach for performing rule-based reasoning about context data targeting AmI systems. For this sake, we defined a context model assuming that in AmI environments context data is distributed over two sides, the user side, represented by the users and their mobile devices, and the ambient side, represented by the fixed computational infrastructure and ambient services. We formalized the cooperative reasoning operation - in which two entities cooperate to perform decentralized rule-based reasoning - and defined a complete process to perform this operation. Finally, to show the feasibility of this approach, we designed, implemented and evaluated a middleware service supporting decentralized reasoning based cooperative reasoning process.