In the Center for Complexity and Collective Computation at the Wisconsin Institute for Discovery
Biological and social systems tend to be hierarchically organized, with multiple functionally relevant spatial and temporal scales. C4 scientists are interested in how and why these scales arise. Results of C4 research suggest that robust, slowly changing social aggregates arise from interactions among self-interested components through a process of collective computation, whereby components minimize uncertainty by coarse-graining over microscopic interactions.
The basic idea is that coarse-grained, statistical representations of collective dynamics are more predictive of the future state of the system than the constantly in-flux behavioral patterns at the component, or microscopic, level. Hence the representations provide a stable background against which components can fine tune their strategies. As an interaction history accumulates the coarse-grained representations--social structure--consolidate. This minimizes environmental uncertainty, can facilitates adaptation, and may provide the foundations for new levels of organization.
Of course in social systems at all scales of biological organization there are multiple components interacting and simultaneously coarse-graining. Hence of interest are the collective consequences for social structure of many components searching for regularities and modulating their strategies in response to perceived regularities. C4 researchers have developed novel computational techniques (Inductive Game Theory) for extracting strategic decision-making rules from time-series data and constructing causal networks or adaptive social circuits that capture these collective effects and so map microscopic dynamics to aggregate-level properties at the macroscopic scale.
C4 scientists believe collective computation might account for how mind emerges from brain and underlies the transitions to new kinds of individuality that have occurred over the history of life on earth. C4 research spans multiple levels of organization in the search for common algorithmic principles underlying the formation of collectives.