Salvato in:
Dettagli Bibliografici
Autori principali: Hansen, Kristoffer Arnsfelt, Ibsen-Jensen, Rasmus, Neyman, Abraham
Natura: Preprint
Pubblicazione: 2025
Soggetti:
Accesso online:https://arxiv.org/abs/2505.02623
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866913820482469888
author Hansen, Kristoffer Arnsfelt
Ibsen-Jensen, Rasmus
Neyman, Abraham
author_facet Hansen, Kristoffer Arnsfelt
Ibsen-Jensen, Rasmus
Neyman, Abraham
contents We study the memory resources required for near-optimal play in two-player zero-sum stochastic games with the long-run average payoff. Although optimal strategies may not exist in such games, near-optimal strategies always do. Mertens and Neyman (1981) proved that in any stochastic game, for any $\varepsilon>0$, there exist uniform $\varepsilon$-optimal memory-based strategies -- i.e., strategies that are $\varepsilon$-optimal in all sufficiently long $n$-stage games -- that use at most $O(n)$ memory states within the first $n$ stages. We improve this bound on the number of memory states by proving that in any stochastic game, for any $\varepsilon>0$, there exist uniform $\varepsilon$-optimal memory-based strategies that use at most $O(\log n)$ memory states in the first $n$ stages. Moreover, we establish the existence of uniform $\varepsilon$-optimal memory-based strategies whose memory updating and action selection are time-independent and such that, with probability close to 1, for all $n$, the number of memory states used up to stage $n$ is at most $O(\log n)$. This result cannot be extended to strategies with bounded public memory -- even if time-dependent memory updating and action selection are allowed. This impossibility is illustrated in the Big Match -- a well-known stochastic game where the stage payoffs to Player 1 are 0 or 1. Although for any $\varepsilon > 0$, there exist strategies of Player 1 that guarantee a payoff {exceeding} $1/2 - \varepsilon$ in all sufficiently long $n$-stage games, we show that any strategy of Player 1 that uses a finite public memory fails to guarantee a payoff greater than $\varepsilon$ in any sufficiently long $n$-stage game.
format Preprint
id arxiv_https___arxiv_org_abs_2505_02623
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Stochastic Games with Limited Public Memory
Hansen, Kristoffer Arnsfelt
Ibsen-Jensen, Rasmus
Neyman, Abraham
Computer Science and Game Theory
Optimization and Control
We study the memory resources required for near-optimal play in two-player zero-sum stochastic games with the long-run average payoff. Although optimal strategies may not exist in such games, near-optimal strategies always do. Mertens and Neyman (1981) proved that in any stochastic game, for any $\varepsilon>0$, there exist uniform $\varepsilon$-optimal memory-based strategies -- i.e., strategies that are $\varepsilon$-optimal in all sufficiently long $n$-stage games -- that use at most $O(n)$ memory states within the first $n$ stages. We improve this bound on the number of memory states by proving that in any stochastic game, for any $\varepsilon>0$, there exist uniform $\varepsilon$-optimal memory-based strategies that use at most $O(\log n)$ memory states in the first $n$ stages. Moreover, we establish the existence of uniform $\varepsilon$-optimal memory-based strategies whose memory updating and action selection are time-independent and such that, with probability close to 1, for all $n$, the number of memory states used up to stage $n$ is at most $O(\log n)$. This result cannot be extended to strategies with bounded public memory -- even if time-dependent memory updating and action selection are allowed. This impossibility is illustrated in the Big Match -- a well-known stochastic game where the stage payoffs to Player 1 are 0 or 1. Although for any $\varepsilon > 0$, there exist strategies of Player 1 that guarantee a payoff {exceeding} $1/2 - \varepsilon$ in all sufficiently long $n$-stage games, we show that any strategy of Player 1 that uses a finite public memory fails to guarantee a payoff greater than $\varepsilon$ in any sufficiently long $n$-stage game.
title Stochastic Games with Limited Public Memory
topic Computer Science and Game Theory
Optimization and Control
url https://arxiv.org/abs/2505.02623