  Natural selection has shaped the evolution of cells and multi-cellular
organisms such that social cooperation can often be preferred over an
individualistic approach to metabolic regulation. This paper extends a
framework for dynamic metabolic resource allocation based on the maximum
entropy principle to spatiotemporal models of metabolism with cooperation. Much
like the maximum entropy principle encapsulates `bet-hedging' behaviour
displayed by organisms dealing with future uncertainty in a fluctuating
environment, its cooperative extension describes how individuals adapt their
metabolic resource allocation strategy to further accommodate limited knowledge
about the welfare of others within a community. The resulting theory explains
why local regulation of metabolic cross-feeding can fulfil a community-wide
metabolic objective if individuals take into consideration an ensemble measure
of total population performance as the only form of global information. The
latter is likely supplied by quorum sensing in microbial systems or signalling
molecules such as hormones in multi-cellular eukaryotic organisms.
