Extending Iterated, Spatialized Prisoner’s Dilemma to Understand Multicellularity: Game Theory With Self-Scaling Players

Abstract

Evolutionary developmental biology, biomedicine, neuroscience, and many aspects of the social sciences are impacted by insight into forces that facilitate the merging of active subunits into an emergent collective. The dynamics of interaction between agents are often studied in game theory, such as the popular Prisoner’s Dilemma (PD) paradigm, but the impact of these models on higher scales of organization, and their contributions to questions of how agents distinguish borders between themselves and the outside world, are not clear. Here we applied a spatialized, iterated PD model to understand the dynamics of the formation of large-scale tissues (colonies that act as one) out of single cell agents. In particular, we broke a standard assumption of PD: instead of a fixed number of players which can Cooperate or Defect on each round, we let the borders of individuality remain fluid, enabling agents to also Merge or Split. The consequences of enabling agents’ actions to change the number of agents in the world result in non-linear dynamics that are not known in advance: would higher-level (composite) individuals emerge? We characterized changes in collective formation as a function of memory size of the subunits. Our results show that when the number of agents is determined by the agents’ behavior, PD dynamics favor multicellularity, including the emergence of structured cell-groups, eventually leading to one single fully-merged tissue. These larger agents were found to have higher causal emergence than smaller ones. Moreover, we observed different spatial distributions of merged connectivity vs. of similar behavioral propensities, revealing that rich but distinct structures can coexist at the level of physical structure and the space of behavioral propensities. These dynamics raise a number of interesting and deep questions about decision-making in a self-modifying system that transitions from a metabolic to a morphological problem space, and how collective intelligences emerge, scale, and pattern.