Does Low Spoilage Under Cold Conditions Foster Cultural Complexity During the Foraging Era? -- A Theoretical and Computational Inquiry

TL;DR

The study investigates whether ecological stability—operationalized as low daily spoilage probability $p$ and high daily yield $Y$—indirectly fosters cultural complexity in foraging-era dynamics. It combines a tractable mathematical model with reinforcement learning simulations to derive and validate a mechanism: reduced spoilage lowers hunting frequency, freeing time for cultural activities and skill development, which in turn enhances future subsistence returns. Empirical-style results from the RL experiments show a strong negative relationship between $p$ and cultural complexity $C$, with yield $Y$ contributing positively but more weakly, consistent with the theoretical proposition. The work provides a formal, computationally grounded link between environmental parameters and cultural elaboration, framing ecological stability as an enabling condition rather than a deterministic driver, and pointing to future work that integrates dynamic ecology and demographic factors.

Abstract

Human cultural complexity did not arise in a vacuum. Scholars in the humanities and social sciences have long debated how ecological factors, such as climate and resource availability, enabled early hunter-gatherers to allocate time and energy beyond basic subsistence tasks. This paper presents a formal, interdisciplinary approach that integrates theoretical modeling with computational methods to examine whether conditions that allow lower spoilage of stored food, often associated with colder climates and abundant large fauna, could indirectly foster the emergence of cultural complexity. Our contribution is twofold. First, we propose a mathematical framework that relates spoilage rates, yield levels, resource management skills, and cultural activities. Under this framework, we prove that lower spoilage and adequate yields reduce the frequency of hunting, thus freeing substantial time for cultural pursuits. Second, we implement a reinforcement learning simulation, inspired by engineering optimization techniques, to validate the theoretical predictions. By training agents in different $(Y,p)$ environments, where $Y$ is yield and $p$ is the probability of daily spoilage, we observe patterns consistent with the theoretical model: stable conditions with lower spoilage strongly correlate with increased cultural complexity. While we do not claim to replicate prehistoric social realities directly, our results suggest that ecologically stable niches provided a milieu in which cultural forms could germinate and evolve. This study, therefore, offers an integrative perspective that unites humanistic inquiries into the origins of culture with the formal rigor and exploratory power of computational modeling.

Figures (4)

• Figure 1: Cultural complexity $C$ as a function of spoilage probability $p$. Each point represents one agent. The red line is a linear fit. As $p$ increases, $C$ declines.
• Figure 2: Cultural complexity $C$ as a function of yield $Y$. Each point represents one agent. The red line is a linear fit. As $Y$ increases, $C$ tends to rise modestly.
• Figure 3: Distribution of cultural complexity $C$ across all agents. Most agents cluster near low or slightly negative $C$ values, but some achieve higher complexity.
• Figure 4: A two-dimensional map showing $C$ as a function of $Y$ (horizontal axis) and $p$ (vertical axis). Colors indicate mean $C$ achieved. Lower $p$ and higher $Y$ environments produce higher $C$.

Theorems & Definitions (6)

• Proposition 1
• proof
• Proposition 2
• proof
• Theorem 1: Cultural Complexity Advantage
• proof