首页> 外文会议>Algorithmic probability and friends: Bayesian prediction and artificial intelligence >An Optimal Superfarthingale and Its Convergence over a Computable Topological Space
【24h】

An Optimal Superfarthingale and Its Convergence over a Computable Topological Space

机译:最优Superfarthingale及其在可计算拓扑空间上的收敛性

获取原文
获取原文并翻译 | 示例

摘要

We generalize the convergenece of the corresponding conditional probabilities of an optimal semimeasure to a real probability in algorithmic probability by using game-theoretic probability theory and the theory of computable topology. Two lemmas in the proof give as corollary the existence of an optimal test and an optimal integral test, which are important from the point of view of algorithmic randomness. We only consider an SCT_3 space, where we can approximate the measure of an open set. Our proof of almost-sure convergence to the real probability by a superfarthingale indicates why the convergence in Martin-Loef sense does not hold.
机译:利用博弈论概率论和可计算拓扑理论,将最优半量度的相应条件概率的收敛性推广到算法概率中的实际概率。证明中的两个引理给出了最优检验和最优积分检验的推论,这从算法随机性的角度来看很重要。我们只考虑一个SCT_3空间,我们可以在其中近似一个开放集的度量。我们关于超级远鸟的几乎肯定收敛到实际概率的证明表明了为什么马丁-洛夫意义上的收敛不成立。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号