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This chapter deals with the implications of rationality in normal form games. It first explores the ramifications of the rationalizability assumption and shows that in many cases rational individuals will not play rationalizable strategies. It argues that the informal reasoning supporting rationalizability must be replaced by a more rigorous analytical framework. This framework is known as epistemic game theory. Using epistemic game theory, it presents the argument that not rationality, but rather common knowledge of rationality, implies that players will only use rationalizable strategies. The chapter concludes by showing that there is no justification of the common knowledge of rationality assumption, and hence there is no reason to believe that in general rational players will choose rationalizable strategies. It strengthens this conclusion by showing that even assuming common knowledge of rationality, there is no reason for a rational player to conform to the iterated elimination of strongly dominated strategies.

This chapter uses epistemic game theory to expand on the notion of social norms as choreographer of a correlated equilibrium, and to elucidate the socio-psychological prerequisites for the notion that social norms implement correlated equilibria. The correlated equilibrium is a much more natural equilibrium criterion than the Nash equilibrium, because of a famous theorem of Aumann (1987), who showed that Bayesian rational agents in an epistemic game G with a common subjective prior play a correlated equilibrium of G. Thus, while rationality and common priors do not imply Nash equilibrium, these assumptions do imply correlated equilibrium and social norms act not only as choreographer, but also supply the epistemic conditions for common priors.

This chapter introduces a modeling language for representing the epistemic states of networked human agents at both the individual and collective levels. The new ‘epistemic description language’, or ‘EDL’, has a graphical component and a syntactical component. The language is used to articulate the relationships between individuals and their beliefs as elementary blocks of interactive epistemic networks. The chapter shows how epinets can be used to capture causally relevant states of social networks, and argue for the compilation of an epistemic description language for social interactions and networks.

This chapter extends the use of epinets to the characterization of dynamic processes in networks. Epinets are employed in two distinct ways: first as instruments for specifying changes in the epistemic states of linked or interacting agents, and second as a toolkit for representing strategic interactions. Using epinets to represent interactions among epistemically-linked agents resolves ambiguities inherent in game theoretic approaches and enables explicit modeling of subtle phenomena including mind games, dialogical games, and information brokerage games.

This chapter considers the Epistemic Description Language (EDL) introduced in the previous chapters through an epistemic prism, offering an interpretation of the development of an epistemic approach to social network analysis as a set of brokering and closure-producing moves, where brokering happens across research communities with different representational and methodological commitments (epistemic game theory, network sociology) and closure acts at the level of a nascent group interested in the epistemic structure and dynamics of networks. The chapter concludes with a discussion of future directions for research and development.

Using examples and unstructured intuitions that highlight the importance of knowledge, beliefs, and mutual beliefs to the outcomes of social situations and interpersonal relations, this chapter argues for the usefulness of epistemic models of human interactions and networks. The notions of an epistemic state – a link between individuals and propositions they may know or believe – and an epistemic tie among individuals – a link connecting individuals’ epistemic states to one another, are introduced. The chapter shows how the structure of epistemic networks formed by such links are relevant to the dynamics of human interactions, and how the dynamics of these networks are critical elements of complex interpersonal narratives.