Conflicts of interest improve collective computation of adaptive social structures.

ABSTRACT: In many biological systems, the functional behavior of a group is collectively computed by the system's individual components. An example is the brain's ability to make decisions via the activity of billions of neurons. A long-standing puzzle is how the components' decisions combine to produce beneficial group-level outputs, despite conflicts of interest and imperfect information. We derive a theoretical model of collective computation from mechanistic first principles, using results from previous work on the computation of power structure in a primate model system. Collective computation has two phases: an information accumulation phase, in which (in this study) pairs of individuals gather information about their fighting abilities and make decisions about their dominance relationships, a

SUBMITTER: Brush ER 

PROVIDER: S-EPMC5777398 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature