In 2008, by building further on our earlier work on classical belief revision, we wrote the paper 'A qualitative theory of dynamic interactive belief revision', in which we combine the work on Dynamic Epistemic Logic to model complex classical multi-agent learning scenarios with the AGM theory to model single-agent belief revision. The result is a new logical setting to model belief revision and belief dynamics, which can cover most examples of multi-agent communication involving belief change that we encountered in the literature. We completely axiomatize our logic and show in our paper how our update mechanism for belief change can actually simulate, in a uniform manner, many different belief-revision policies. The paper illustrates explicitly how an agent's different epistemic and doxastic attitudes (his/her different notions of weak and strong belief and types of knowledge) can be represented in unified single framework. The paper links to the main debates in formal epistemology on qualitative notions of knowledge, showing the connections between different epistemic concepts. Moreover, our setting ties in with work on models of non-monotonic reasoning scenarios in the area of multi-agent systems in AI.