Ellsberg's (1961) seminal experiment established that ambiguity and ambiguity aversion are phenomena that can impact decision making in situations where objective probabilities of events are not readily available. Since the seminal papers of Schmeidler (1989) and Gilboa and Schmeidler (1989), a vast literature has developed studying decision-making under ambiguity and providing different models that capture Ellsberg's findings. The application of such models to situations of dynamic interactions is however complicated by several issues. (i) There is no unique generalization of the Bayesian updating rule to non-additive probabilities. (ii) Related to this, since Bayesian updating is necessary for dynamic consistency, most models of decision making under ambiguity exhibit dynamically inconsistent behavior. (iii) Models of dynamic interaction, either in markets or in games, use equilibrium concepts, which require the specification of expectations about others' behavior or the future values of endogenous variables, such as prices. Reformulating the notion of rational expectations in the context of ambiguity, and exploring in how far rational expectations are feasible in such settings presents a further challenge. (iv) Finally, dynamic models naturally involve the issue of learning about exogenous or endogenous variables. Models of learning under ambiguity are still sparse and generate different predictions about the outcome of such a learning process. The goal of the Round Table on Ambiguity in Dynamic Interactions is to shed light on the latest developments in the applications of models of ambiguity and ambiguity aversion in situations of dynamic interactions and identify paths for future development. Experimental and empirical evidence from markets and games has demonstrated that ambiguity-aversion can explain deviations from the predictions of standard models. The session will review some of this evidence as a motivation for incorporating ambiguity and ambiguity-attitudes into economic models and will provide a discussion in how far such attitudes can be considered rational as compared to the standard Savage / Bayes framework. Next, the main results of incorporating ambiguity in models of financial markets, games and environmental policy will be presented and discussed. We will talk about methodological issues, about the extent to which ambiguity affects classical results in markets and games, as well as about the persistence of such effects. Finally, the impact of ambiguity on policy making will be discussed in the context of environmental regulation.