Modeling synthetic characters which interact with objects in dynamic virtual worlds is important when we want the agents to act in an autonomous and non-preplanned way. Such interactions with objects would allow the synthetic characters to behave in a more believable way. Once objects offer innumerous uses, it is essential that the agent is able to acquire the necessary knowledge to identify action possibilities in the objects while interacting with them. We propose a conceptual framework that allows the agents to identify possible interactions with objects based in past experiences with other objects. Starting from sensory patterns collected during interactions with objects, the agent is able to acquire conceptual knowledge about regularities of the world, its internal states and its own actions. The presented work also proposes that such acquired knowledge may be used by the agent in order to satisfy its needs and goals by interacting with objects. Preliminary tests were made and it...