Does Low Spoilage Under Cold Conditions Foster Cultural Complexity During the Foraging Era?—Agent-Based Modeling and Reinforcement-Learning Approach

초록

Human cultural complexity did not arise in a vacuum. This study employs agent-based modeling (ABM) and ecological modeling perspectives, combined with reinforcement-learning techniques, to investigate whether conditions that allowed for the lower spoilage of stored food, often associated with colder climates and abundant large fauna, might have indirectly fostered the emergence of cultural complexity. Specifically, we developed a mathematical framework to capture how spoilage rates, yield levels, resource management skills, and cultural activities interact within a multi-agent system. Under the restrictive constraints, we proved that lower spoilage and adequate yields reduced the frequency of hunting, freeing time for cultural pursuits. We then implemented a reinforcement-learning simulation to validate these predictions by training agents in different (Formula presented.) environments, where Y is the yield and p is the probability of daily spoilage. Our regression analysis and visualizations showed strong correlations between stable conditions with lower spoilage and higher levels of cultural investment. While we do not claim to replicate prehistoric social realities directly, our findings highlight the potential of ABM and ecological modeling to illuminate how environmental factors influence the allocation of time to complex cultural activities. This work offers a computationally grounded perspective that bridges humanistic inquiries into the origins of culture with formal agent-based methods. © 2025 by the author.

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