Escalation of Memory Length in Finite Populations

Area of Science:

• Evolutionary biology
• Computational simulation
• Complex systems

Background:

• Coevolutionary systems are theorized to increase complexity, but simulations struggle to demonstrate this.
• Previous models, like Lindgren's, showed limitations in escalating memory length for cooperative strategies.

Purpose of the Study:

• To establish criteria for coevolutionary systems to exhibit escalation of strategic complexity.
• To overcome limitations in existing models regarding the escalation of memory length.
• To investigate the role of population size and complexity transitions in coevolutionary escalation.

Main Methods:

• Drawing on macroevolutionary theory to define criteria for escalation.
• Expanding a previously developed model of memory length evolution.
• Conducting long-term coevolutionary simulations with varied population sizes.

Main Results:

• Larger population sizes significantly support greater escalation of complexity.
• Extended operators of evolutionary variation resolved limitations in memory length escalation.
• Coevolutionary arms races can continue to escalate in simulations with sufficient population sizes.

Conclusions:

• Coevolutionary systems can achieve escalation of strategic complexity.
• Sufficient population size is crucial for overcoming limitations in computational coevolutionary models.
• The study provides a framework and evidence for sustained escalation in coevolutionary arms races.