Across math, statistical mechanics, and neural networks, the work shows cooperation can arise in simple scenarios.

A major theoretical contribution accompanies the results: a generalization of Fisher’s fundamental theorem of natural selection in evolutionary dynamics.

The study presents a generalized Fisher theorem as a central theoretical advance.

A Rutgers-led study challenges the notion that selfishness dominates, showing cooperation can emerge without enforcement or kinship.

The PNAS publication demonstrates cooperation can arise naturally in the Prisoner’s Dilemma without extra rules, genetic ties, or kinship.

Beyond biology, the findings could inform understanding of cooperation in human societies and other complex systems.

The research uses mathematical models and computer simulations, including neural networks playing repeated games, to explore how recognition and memory promote cooperative behavior.

Neural networks simulate repeated Prisoner’s Dilemma games, supporting the idea that opponent-specific reactions foster cooperation.

Morozov and Feigel apply interdisciplinary methods, linking cognitive-like recognition to emergent cooperative behavior.

The framework generalizes to multi-system cooperation, suggesting periods of stability and upheaval over time.

Led by Alexandre Morozov and Alexander Feigel, the work was published in the Proceedings of the National Academy of Sciences.

The Rutgers work argues cooperation can spontaneously emerge without kinship or group selection, reshaping classic views.