How can our societies be stabilized in a crisis? Why do we enjoy and understand Shakespeare? Why are fruitflies uniform? How do omnivorous eating habits aid our survival? What makes the Mona Lisa's smile beautiful? How do women keep their social structures intact? -- Could there possibly be a single answer to all these questions? This book shows that the statement 'weak links stabilize complex systems' provides the key to understanding each of these intriguing puzzles, and many others too. The (...) author...uses weak (low affinity, low probability) interactions as a thread to introduce a vast variety of networks from proteins to economics and ecosystems. --From publisher description. (shrink)

The network concept is increasingly used for the description of complex systems. Here, we summarize key aspects of the evolvability and robustness of the hierarchical network set of macromolecules, cells, organisms and ecosystems. Listing the costs and benefits of cooperation as a necessary behaviour to build this network hierarchy, we outline the major hypothesis of the paper: the emergence of hierarchical complexity needs cooperation leading to the ageing (i.e. gradual deterioration) of the constituent networks. A stable environment develops cooperation leading (...) to over‐optimization, and forming an ‘always‐old’ network, which accumulates damage, and dies in an apoptosis‐like process. A rapidly changing environment develops competition forming a ‘forever‐young’ network, which may suffer an occasional over‐perturbation exhausting system resources, and causing death in a necrosis‐like process. Giving a number of examples we demonstrate how cooperation evokes the gradual accumulation of damage typical to ageing. Finally, we show how various forms of cooperation and consequent ageing emerge as key elements in all major steps of evolution from the formation of protocells to the establishment of the globalized, modern human society. (shrink)

I hypothesize that re-occurring prior experience of complex systems mobilizes a fast response, whose attractor is encoded by their strongly connected network core. In contrast, responses to novel stimuli are often slow and require the weakly connected network periphery. Upon repeated stimulus, peripheral network nodes remodel the network core that encodes the attractor of the new response. This “core-periphery learning” theory reviews and generalizes the heretofore fragmented knowledge on attractor formation by neural networks, periphery-driven innovation, and a number of recent (...) reports on the adaptation of protein, neuronal, and social networks. The core-periphery learning theory may increase our understanding of signaling, memory formation, information encoding and decision-making processes. Moreover, the power of network periphery-related “wisdom of crowds” inventing creative, novel responses indicates that deliberative democracy is a slow yet efficient learning strategy developed as the success of a billion-year evolution. Also see the video abstract here: https://youtu.be/IIjP7zWGjVE. The network core triggers fast responses to previously experienced stimuli. Innovations require the network periphery that encodes a novel attractor by core-remodeling. This core-periphery learning theory is introduced as a general adaptation, learning, decision-making, and forgetting mechanism of all complex systems including protein, metabolic, signaling, neuronal, social networks, and ecosystems. (shrink)