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Interdependent Self-Organizing Mechanisms for Cooperative Survival.

Matthew Scott1, Jeremy Pitt2

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Cooperative survival games require collective action amidst catastrophes. Artificial societies reveal that increased complexity and uncertainty necessitate greater self-organization opportunities for survival, with mechanisms interacting in complex ways.

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Area of Science:

  • Artificial Societies
  • Game Theory
  • Complex Systems

Background:

  • Cooperative survival games present challenges due to recurring catastrophes and resource management complexities.
  • Self-organization is crucial for sustainability and survival in social systems.

Purpose of the Study:

  • Investigate the effectiveness of socially constructed self-organization in cooperative survival games using artificial societies.
  • Analyze the impact of scale, uncertainty, complexity, and opportunity on survival outcomes.

Main Methods:

  • Designed and implemented a multiagent system simulating a cooperative survival scenario.
  • Integrated three entangled subgames: stag hunt, common-pool resource management, and collective risk dilemma.
  • Specified algorithms for governance, trading, and forecasting self-organizing mechanisms.

Main Results:

  • Identified a critical mass threshold for survivor numbers.
  • Demonstrated that higher uncertainty and complexity demand increased self-organization opportunities.
  • Observed both detrimental and beneficial interactions among self-organizing mechanisms.

Conclusions:

  • Self-organization is vital for navigating complex survival scenarios with uncertainty.
  • The interplay of self-organizing mechanisms requires careful consideration for effective collective governance.
  • Further research into adaptive self-organization strategies is warranted for long-term survival.