Knowledge, probability, and adversaries
Knowledge, probability, and adversaries
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知识、概率和对手
DOI：
10.1145/153724.153770
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发表时间：
1993
期刊：
影响因子：
--
通讯作者：
M. Tuttle
中科院分区：
文献类型：
--
作者：
Joseph Y. Halpern;M. Tuttle
对于一个代理人来说，知道或相信一个断言以9.99的概率为真意味着什么？不同的论文[2，6，15]给出了不同的答案，在计算代理分配给事件的概率时选择使用完全不同的概率空间。我们表明，每一个选择可以理解的赌博游戏。这种赌博游戏本身可以理解为三种类型的对手影响游戏的三个不同方面。第一个选择系统中所有不确定性选择的结果;第二个表示博弈中代理对手的知识（这是上面提到的论文不同的关键地方）;第三个在异步系统中需要选择下注的时间。我们举例说明需要考虑所有三种类型的对手。给定一类对手，我们展示了如何分配概率空间的代理最适合该类，其中“最合适”是精确的，在这个赌博游戏。最后，我们展示了不同的概率空间分配（对应于不同的对手）如何在概率协同攻击中产生不同程度的保证。
What should it mean for an agent to know or believe an assertion is true with probability 9.99? Different papers [2, 6, 15] give different answers, choosing to use quite different probability spaces when computing the probability that an agent assigns to an event. We show that each choice can be understood in terms of a betting game. This betting game itself can be understood in terms of three types of adversaries influencing three different aspects of the game. The first selects the outcome of all nondeterministic choices in the system; the second represents the knowledge of the agent's opponent in the betting game (this is the key place the papers mentioned above differ); and the third is needed in asynchronous systems to choose the time the bet is placed. We illustrate the need for considering all three types of adversaries with a number of examples. Given a class of adversaries, we show how to assign probability spaces to agents in a way most appropriate for that class, where “most appropriate” is made precise in terms of this betting game. We conclude by showing how different assignments of probability spaces (corresponding to different opponents) yield different levels of guarantees in probabilistic coordinated attack.