Modeling evidential cooperation in large worlds
Johannes Treutlein

TL;DR
This paper develops a game-theoretic model of evidential cooperation in large worlds, exploring how agents with uncertain values can benefit from cooperation, and analyzes equilibrium concepts and stability issues.
Contribution
It introduces a formal model of ECL as an incomplete information bargaining problem, incorporating dependency equilibria and analyzing the relevance of the Nash bargaining solution.
Findings
All cooperators should maximize the same weighted utility sum for Pareto optimality.
The Nash bargaining solution can serve as a Schelling point in ECL.
Gains from trade decrease as belief in other agents diminishes.
Abstract
Evidential cooperation in large worlds (ECL) refers to the idea that humans and other agents can benefit by cooperating with similar agents with differing values in causally disconnected parts of a large universe. Cooperating provides agents with evidence that other similar agents are likely to cooperate too, resulting in gains from trade for all. This could be a crucial consideration for altruists. I develop a game-theoretic model of ECL as an incomplete information bargaining problem. The model incorporates uncertainty about others' value systems and empirical situations, and addresses the problem of selecting a compromise outcome. Using the model, I investigate issues with ECL and outline open technical and philosophical questions. I show that all cooperators must maximize the same weighted sum of utility functions to reach a Pareto optimal outcome. However, I argue against…
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Taxonomy
TopicsExperimental Behavioral Economics Studies · Economic Theory and Institutions · Economic theories and models
