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In the great family of distributed applications, collaborative systems are distinguished by the fact that users, usually agents, are working together to fulfill a common goal. Therefore they have a critical need to interact closely with each other through: information exchange, sharing of applications, control of some over others, and sharing computer resources, among others. However, the success of achieving the common goal depends on the implementation of appropriate collaborations in these dynamic distributed environments. But proper collaborations also depend on several factors that have to do, mainly, with the way in which the environment is at any given time, as well as provide answers to questions like: "With whom it must collaborate?" "Who should collaborate?" On the other hand, awareness is a process where users recognize each other's activities with the promise of co-presence, for example, "What are they doing?", "Where are they?" This paper describes a learning model for collaborative distributed environments that takes into account the experience of awareness collaborations occurring in the environment for achieving the most appropriate future awareness situations.