Decision making in stochastic extensive form II: Stochastic extensive forms and games
Abstract
A general theory of stochastic extensive forms is developed to bridge two concepts of information flow: decision trees and refined partitions on the one side, filtrations from probability theory on the other. Instead of the traditional "nature" agent, this framework uses a single lottery draw to select a tree of a given decision forest. Each "personal" agent receives dynamic updates from an own oracle on the lottery outcome and makes partition-refining choices adapted to this information. This theory addresses a key limitation of existing approaches in extensive form theory, which struggle to model continuous-time stochastic processes, such as Brownian motion, as outcomes of "nature" decision making. Additionally, a class of stochastic extensive forms based on time-indexed action paths is constructed, encompassing a wide range of models from the literature and laying the groundwork for an approximation theory for stochastic differential games in extensive form.
Cite
@article{arxiv.2411.17587,
title = {Decision making in stochastic extensive form II: Stochastic extensive forms and games},
author = {E. Emanuel Rapsch},
journal= {arXiv preprint arXiv:2411.17587},
year = {2024}
}
Comments
51 pages (76 pages with appendix), second part of a three-paper series, for Part I see arXiv:2404.12332. arXiv admin note: text overlap with arXiv:2404.12332