337 | Kevin Zollman on Game Theory, Signals, and Meaning

What It Covers

Kevin Zollman explains how game theory mathematically models strategic interactions across humans, animals, and organisms, revealing insights about cooperation, signaling, evolutionary dynamics, and the origins of meaning, language, and conventions through computational simulations.

Key Questions Answered

• •Utility Functions: Von Neumann and Morgenstern created measurable utilities by asking people to compare gambles between three items, determining preference intensity through risk tolerance. This mathematical framework enables quantifying choices across tea versus coffee decisions to complex strategic situations.
• •Ultimatum Game Applications: When one person proposes splitting money and another accepts or rejects, people sacrifice thirty dollars to punish unfairness but accept three million despite inequity. This reveals how fairness preferences interact with monetary motivations across different scales.
• •Tit-for-Tat Strategy: In repeated prisoner's dilemmas, starting with cooperation then mirroring opponent's previous move creates sustained cooperation through punishment threats. This remarkably simple algorithm outperformed complex strategies in Axelrod's tournament, requiring only opponent recognition to function effectively.
• •Signaling Without Costs: Traditional handicap principle predicted costly signals prove quality, but field measurements found insufficient costs. New hybrid equilibrium theory shows hummingbirds randomize female coloration evolutionarily, with some females adopting male colors despite being female, matching predictions.
• •Language as Coordination: Meaning emerges from game-theoretic coordination rather than intentionality. When someone asks "can you pass the salt," the literal ability question becomes a request because caring about ability only matters if wanting action, enabling naturalistic explanations.