On the Foundations of Dynamic Games and Probability: Decision Making in Stochastic Extensive Form
E. Emanuel Rapsch

TL;DR
This paper develops a comprehensive abstract framework for dynamic games under probabilistic uncertainty, integrating decision trees, exogenous information, and stochastic processes to address complex decision-making scenarios over time.
Contribution
It introduces stochastic decision forests and extensive forms, generalizing previous models and providing a foundation for continuous-time stochastic game analysis.
Findings
Characterization of well-posedness via order-theoretic properties
Development of a stochastic process form for extensive games
Application to stochastic differential and timing games
Abstract
In this work, an abstract and general language for the fundamental objects underlying dynamic games under probabilistic uncertainty is developed. Combining the theory of decision trees by Al\'os-Ferrer--Ritzberger (2005) and a Harsanyian notion of exogenous uncertainty, the concept of stochastic decision forests is introduced. Exogenous information is modelled via filtration-like objects providing dynamic updates on the "realised tree", and an abstract decision-theoretic model of adapted choice is formulated. Based on this, a consistent model of "rules" is introduced, leading to the notion of stochastic extensive forms, generalising the works of Al\'os-Ferrer--Ritzberger (2008, 2011). Well-posedness is completely characterised in terms of order-theoretic properties of the underlying forest. Moreover, the language of stochastic extensive forms addresses a vast class of dynamic decision…
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