Small steps for mankind: Modeling the emergence of cumulative culture from joint active inference communication discusses a testable deep active inference formulation of social behavior and accompanying simulations of cumulative culture in two steps: First: cast cultural transmission as a bi-directional process of communication that induces a generalized synchrony (operationalized as a particular convergence) between the belief states of interlocutors. Second: cast social or cultural exchange as a process of active inference by equipping agents with the choice of who to engage in communication with. This induces trade-offs between confirmation of current beliefs and exploration of the social environment. Cumulative culture emerges from belief updating (i.e., active inference and learning) in the form of a joint minimization of uncertainty. The emergent cultural equilibria are characterized by a segregation into groups, whose belief systems are actively sustained by selective, uncertainty minimizing, dyadic exchanges. The nature of these equilibria depends sensitively on the precision afforded by various probabilistic mappings in each individual’s generative model of their encultured niche.
Active inference allows us to formulate a normative and explainable account of cultural information spread through communication by casting cultural transmission as a bi-directional communicative process that entails a particular convergence between distinct conveyors and conveners of cultural information.
Agents differ in their action model of which agent to visit at each time point. Their individual choices are guided by expected free energy (G) which entails maximizing the expected utility of an action (known as pragmatic value) as well as maximizing the expected information gain (known as epistemic value). These two values constrain each other such that maximizing both simultaneously is partially (but not entirely) paradoxical (as illustrated in following figure). These constraints may also be understood as formalizing the exploration-exploitation trade-off, where epistemic value (exploration) refers to the benefit of searching to get a better estimation of promising areas that offer pragmatic value (exploitation)
This formulation employed a Bayesian framework—known as active inference—to formally account for the dynamics underlying (local) communication and (global) cumulative culture dynamics, thus contributing to the ever-growing body of research on multi-agent Bayesian models and collective active inference. The social “transmission” of cultural information has been cast as a fundamentally bidirectional process of communication, which has been shown in the previous active inference literature to induce a generalized synchrony between the internal (belief) states of agents holding sufficiently similar generative models. Building on this work, we operationalized generalized synchrony as a particular convergence between the internal states of interlocutors, and show that it depends sensitively on the precision of observation or likelihood mappings in a generative model of communicative exchange. When we simulate a population of agents that simultaneously engage in communication over time, cumulative culture emerges as the collective behavior brought about by local belief updating (active inference and learning in a dyadic setting). Simulations show that when a divergent belief is introduced to the status quo, it spreads within the population and brings about a collective behavior characterized by a certain degree of segregation between different belief groups. The level to which the status quo population defects to the divergent belief is mediated by local psychological biases for confirmation bias (as directly manipulated) and novelty seeking (as emergent from procedural generation of parameters). These cultural (c.f., voting) equilibria are minimizers of collective or joint free energy that emerge from the imperative to minimize uncertainty and surprise in dyadic exchanges.