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arXiv 2405.09406cs.GT
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部分信息博弈中的有界记忆策略

Bounded-Memory Strategies in Partial-Information Games

Sougata Bose, Rasmus Ibsen-Jensen, Patrick Totzke

AI总结:

该研究针对部分信息随机博弈,证明了有界记忆下零和值近似的NP难度,给出了多人博弈ε-Nash均衡存在性判定及求解的复杂度上界,改进了多类特殊博弈的研究结论。

摘要:

我们研究了求解具有均值收益目标的随机博弈的计算复杂度。我们并未界定那些简单策略足以实现ε-最优性或构成ε-Nash均衡的特殊博弈类别,而是研究通用的部分信息多人博弈,探究在记忆不超过给定上限的前提下,使用有限记忆策略(及对抗有限记忆策略)能达成怎样的效果。我们证明,即使是针对无记忆策略和单人可达性博弈,近似零和值的问题也具有NP难度。另一方面,我们给出了求解任意固定玩家数k的博弈的复杂度上界。我们证明,对于给定的k人博弈、ε≥0以及记忆上限b,判断是否存在所有策略最多使用b个记忆模式的ε-Nash均衡,可在多项式空间内完成。对于给定的ε>0,求解满足b-有界策略约束的ε-Nash均衡可在FN[NP]复杂度类内完成。类似地,在双人零和博弈中,寻找一个b-有界策略,使其在对抗所有b-有界对手策略时,能保证结果与给定值的偏差在ε以内,该问题可在FNP[NP]复杂度类内求解。我们的构造仅需最小程度的简化,即可适用于奇偶性目标。我们的结果改进了多个知名特殊博弈类别的现有研究结论。具体而言,对于双人零和并发均值收益博弈,可在FNP[NP]复杂度内近似求解常规零和值(无需限制可采纳策略)。

英文摘要:

We study the computational complexity of solving stochastic games with mean-payoff objectives. Instead of identifying special classes in which simple strategies are sufficient to play $ε$-optimally, or form $ε$-Nash equilibria, we consider general partial-information multiplayer games and ask what can be achieved with (and against) finite-memory strategies up to a {given} bound on the memory. We show $NP$-hardness for approximating zero-sum values, already with respect to memoryless strategies and for 1-player reachability games. On the other hand, we provide upper bounds for solving games of any fixed number of players $k$. We show that one can decide in polynomial space if, for a given $k$-player game, $ε\ge 0$ and bound $b$, there exists an $ε$-Nash equilibrium in which all strategies use at most $b$ memory modes. For given $ε>0$, finding an $ε$-Nash equilibrium with respect to $b$-bounded strategies can be done in $FN[NP]$. Similarly for 2-player zero-sum games, finding a $b$-bounded strategy that, against all $b$-bounded opponent strategies, guarantees an outcome within $ε$ of a given value, can be done in $FNP[NP]$. Our constructions apply to parity objectives with minimal simplifications. Our results improve the status quo in several well-known special cases of games. In particular, for $2$-player zero-sum concurrent mean-payoff games, one can approximate ordinary zero-sum values (without restricting admissible strategies) in $FNP[NP]$.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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