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.

自然选择塑造了细胞和多细胞生物的进化，因此社会合作通常比个人主义的代谢调节方法更受欢迎。本文将基于最大熵原理的动态代谢资源分配框架扩展到合作的代谢时空模型。就像最大熵原理封装了生物体在波动环境中处理未来不确定性所表现出的“对冲”行为一样，它的合作扩展描述了个体如何调整其代谢资源分配策略以进一步适应对社区内其他人福利的有限了解. 由此产生的理论解释了为什么如果个体将总体人口表现的整体测量作为全球信息的唯一形式，那么代谢交叉喂养的局部调节可以实现社区范围的代谢目标。后者可能由微生物系统中的群体感应或多细胞真核生物中的激素等信号分子提供。