"When conflict breaks out in social groups, individuals make strategic decisions about how to behave based on their understanding of alliances and feuds in the group. (...) In a new study, scientists at the Wisconsin Institute for Discovery (WID) at the University of Wisconsin-Madison develop a computational approach to determine whether individuals behave predictably. With data from previous fights, the team looked at how much memory individuals in the group would need to make predictions themselves. The analysis proposes a novel estimate of "cognitive burden," or the minimal amount of information an organism needs to remember to make a prediction. The research draws from a concept called "sparse coding," or the brain's tendency to use fewer visual details and a small number of neurons to stow an image or scene. Previous studies support the idea that neurons in the brain react to a few large details such as the lines, edges and orientations within images rather than many smaller details. (...)" - Amira

"What is the trade-off? What's the minimum amount of 'stuff' an individual has to remember to make good inferences about future events?" (...) By recording individuals' involvement -- or lack thereof -- in fights, the group created models that mapped the likelihood any number of individuals would engage in conflict in hypothetical situations. (...) Since the statistical modeling and computation frameworks can be applied to different natural datasets, the research has the potential to influence other fields of study, including behavioral science, cognition, computation, game theory and machine learning. Such models might also be useful in studying collective behaviors in other complex systems, ranging from neurons to bird flocks. Future research will seek to find out how individuals' knowledge of alliances and feuds fine-tunes their own decisions and change the groups' collective pattern of conflict." - Amira