Value-Based Distance Between Information Structures
Fabien Gensbittel (TSE), Marcin Peski, J\'er\^ome Renault (TSE)

TL;DR
This paper introduces a new way to measure the difference between information structures based on their impact on game outcomes, providing insights into information value, convergence, and solving longstanding problems in game theory.
Contribution
It offers a tractable characterization of the value-based distance between information structures and addresses key open problems in the theory of information in games.
Findings
The distance relates to the value difference in zero-sum games.
Convergence in this distance aligns with belief hierarchy convergence.
Existence of large, separated sequences of information structures disproves certain continuity assumptions.
Abstract
We define the distance between two information structures as the largest possible difference in value across all zero-sum games. We provide a tractable characterization of distance and use it to discuss the relation between the value of information in games versus single-agent problems, the value of additional information, informational substitutes, complements, or joint information. The convergence to a countable information structure under value-based distance is equivalent to the weak convergence of belief hierarchies, implying, among other things, that for zero-sum games, approximate knowledge is equivalent to common knowledge. At the same time, the space of information structures under the value-based distance is large: there exists a sequence of information structures where players acquire increasingly more information, and > 0 such that any two elements of the sequence…
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