We will present a framework for integration of inductive learning and argumentation, and we will discuss several applications. The argumentation process provides a structured communication protocol to exchange relevant information about an issue between learning agents, while inductive inference provides support for an empirical method for belief revision. Inductive learning offers the possibility of learning general rules, or hypotheses, which describe sets of particular instances. Such rules can be used as arguments inside an argumentation framework. Thus, our proposal consists of an empirical argumentation framework, where arguments are generated through inductive processes by learning from examples.