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Minimax functions on Galton–Watson trees

Part of: Game theory Markov processes Stochastic processes

Published online by Cambridge University Press:  06 December 2019

James B. Martin  and
Roman Stasiński
James B. Martin
Affiliation:
Department of Statistics, University of Oxford, Oxford OX1 3LB, UK Email: martin@stats.ox.ac.uk
Roman Stasiński
Affiliation:
Department of Statistics, University of Oxford, Oxford OX1 3LB, UK Email: martin@stats.ox.ac.uk
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Abstract

We consider the behaviour of minimax recursions defined on random trees. Such recursions give the value of a general class of two-player combinatorial games. We examine in particular the case where the tree is given by a Galton–Watson branching process, truncated at some depth 2n, and the terminal values of the level 2n nodes are drawn independently from some common distribution. The case of a regular tree was previously considered by Pearl, who showed that as n → ∞ the value of the game converges to a constant, and by Ali Khan, Devroye and Neininger, who obtained a distributional limit under a suitable rescaling.

For a general offspring distribution, there is a surprisingly rich variety of behaviour: the (unrescaled) value of the game may converge to a constant, or to a discrete limit with several atoms, or to a continuous distribution. We also give distributional limits under suitable rescalings in various cases.

We also address questions of endogeny. Suppose the game is played on a tree with many levels, so that the terminal values are far from the root. To be confident of playing a good first move, do we need to see the whole tree and its terminal values, or can we play close to optimally by inspecting just the first few levels of the tree? The answers again depend in an interesting way on the offspring distribution.

We also mention several open questions.

MSC classification

Primary: 60J80: Branching processes (Galton-Watson, birth-and-death, etc.)
Secondary: 60G99: None of the above, but in this section 91A46: Combinatorial games
Type
Paper
Information
Combinatorics, Probability and Computing , Volume 29 , Issue 3 , May 2020 , pp. 455 - 484
Copyright
© Cambridge University Press 2019

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