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Qualitative Concurrent Parity Games: Bounded Rationality

机译:定性并发平价博弈:有限理性

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We study two-player concurrent games on finite-state graphs played for an infinite number of rounds, where in each round, the two players (player 1 and player 2) choose their moves independently and simultaneously; the current state and the two moves determine the successor state. The objectives are ω-regular winning conditions specified as parity objectives. We consider the qualitative analysis problems: the computation of the almost-sure and limit-sure winning set of states, where player 1 can ensure to win with probability 1 and with probability arbitrarily close to 1, respectively. In general the almost-sure and limit-sure winning strategies require both infinite-memory as well as infinite-precision (to describe probabilities). While the qualitative analysis problem for concurrent parity games with infinite-memory, infinite-precision randomized strategies was studied before, we study the bounded-rationality problem for qualitative analysis of concurrent parity games, where the strategy set for player 1 is restricted to bounded-resource strategies. In terms of precision, strategies can be deterministic, uniform, finite-precision, or infinite-precision; and in terms of memory, strategies can be memoryless, finite-memory, or infinite-memory. We present a precise and complete characterization of the qualitative winning sets for all combinations of classes of strategies. In particular, we show that uniform memoryless strategies are as powerful as finite-precision infinite-memory strategies, and infinite-precision memoryless strategies are as powerful as infinite-precision finite-memory strategies. We show that the winning sets can be computed in O(n~(2d+3)) time, where n is the size of the game structure and 2d is the number of priorities (or colors), and our algorithms are symbolic. The membership problem of whether a state belongs to a winning set can be decided in NP ∩ coNP. Our symbolic algorithms are based on a characterization of the winning sets as μ-calculus formulas, however, our μ-calculus formulas are crucially different from the ones for concurrent parity games (without bounded rationality); and our memoryless witness strategy constructions are significantly different from the infinite-memory witness strategy constructions for concurrent parity games.
机译:我们在无限次回合上的有限状态图上研究两人同时进行的游戏,其中每一回合中,两名玩家(玩家1和玩家2)分别并同时选择他们的移动;当前状态和这两个动作确定了后继状态。目标是指定为平价目标的ω-常规获胜条件。我们考虑定性分析问题:近似确定和极限确定获胜状态集的计算,其中玩家1可以确保分别以概率1和任意接近1的概率获胜。通常,几乎确定和极限确定的获胜策略既需要无限内存,又需要无限精度(以描述概率)。虽然之前研究了具有无限内存的并发奇偶性游戏的定性分析问题,但无穷精度随机策略,但我们研究了用于并发奇偶性游戏的定性分析的有界理性问题,其中为玩家1设置的策略仅限于有界游戏。资源策略。在精度方面,策略可以是确定性的,统一的,有限精度的或无限精度的。就内存而言,策略可以是无内存,有限内存或无限内存。我们为策略类别的所有组合提供了定性获胜集的精确而完整的特征。尤其是,我们证明了统一的无记忆策略与有限精度无限内存策略一样强大,而无限制的无记忆策略与无限精度无限内存策略一样强大。我们证明获胜集可以在O(n〜(2d + 3))的时间内计算,其中n是游戏结构的大小,2d是优先级(或颜色)的数量,并且我们的算法是象征性的。可以在NP∩coNP中确定状态是否属于获胜集的成员资格问题。我们的符号算法基于获胜集的特征,即μ-演算公式,但是,我们的μ-演算公式与并发奇偶游戏的公式极为不同(无界理性);而且我们的无记忆见证策略构造与并发平价游戏的无限内存见证战略构造显着不同。

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