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How many strings are easy to predict?

机译:容易预测多少个字符串?

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It is well known in the theory of Kolmogorov complexity that most strings cannot be compressed; more precisely, only exponentially few (Theta(2(n-m))) binary strings of length n can be compressed by m bits. This paper extends the 'incompressibility' property of Kolmogorov complexity to the 'unpredictability' property of predictive complexity. The 'unpredictability' property states that predictive complexity (defined as the loss suffered by a universal prediction algorithm working infinitely long) of most strings is close to a trivial upper bound (the loss suffered by a trivial minimax constant prediction strategy). We show that only exponentially few strings can be successfully predicted and find the base of the exponent. (c) 2005 Elsevier Inc. All rights reserved.
机译:在Kolmogorov复杂度理论中众所周知,大多数字符串无法压缩。更准确地说,长度为n的指数串(Theta(2(n-m)))二进制字符串只能压缩m个位。本文将Kolmogorov复杂度的“不可压缩性”性质扩展到预测复杂性的“不可预测性”性质。 “不可预测性”属性指出,大多数字符串的预测复杂度(定义为无限长的通用预测算法所遭受的损失)接近琐碎的上限(琐碎的minimax常数预测策略所遭受的损失)。我们表明,只有很少的几条字符串可以成功地预测并找到指数的基础。 (c)2005 Elsevier Inc.保留所有权利。

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