摘要翻译：
信息论已经解释了许多生物现象的组织，从感觉感受野的生理学到某些DNA序列组合的变异性。一些学者提出，信息应该是生物学中的中心解释原则，因为任何对有机体生存最优的行为策略都必须涉及有效的信息处理。我们通过提供一个反例来挑战这一观点。我们提出了一个可解析的模型，用于感知-行动循环的一个特殊实例：一个生物在一维环形世界中寻找食物来源。该模型包含了生物世界的统计结构、生物行为对该结构的影响以及生物的战略决策过程。该模型表现为无限维状态空间上的马尔可夫过程。为了分析它，我们构造了一个精确的粗粒度化，将模型简化为有限个“信息状态”上的马尔可夫过程。这种技术允许我们在食物收集任务中对一个信息理论上最优的策略和其他候选策略的性能进行定量比较。我们发现：1。信息最优搜索并不一定优化效用（预期粮食收益）。2.根据信息性能对搜索策略进行排序，并不能根据期望获得的食物来预测搜索策略的排序。3.不同战略的相对优势取决于环境的统计结构，特别是来源运动的可变性。我们得出结论，信息和效用之间不存在简单的关系。行为最优性并不意味着信息效率，也不存在获取食物来源信息与获取食物本身之间的简单权衡。
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英文标题：
《Information Maximization Fails to Maximize Expected Utility in a Simple
  Foraging Model》
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作者：
Edward K. Agarwala, Hillel J. Chiel, Peter J. Thomas
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最新提交年份：
2010
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分类信息：

一级分类：Quantitative Biology        数量生物学
二级分类：Other Quantitative Biology        其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
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一级分类：Computer Science        计算机科学
二级分类：Information Theory        信息论
分类描述：Covers theoretical and experimental aspects of information theory and coding. Includes material in ACM Subject Class E.4 and intersects with H.1.1.
涵盖信息论和编码的理论和实验方面。包括ACM学科类E.4中的材料，并与H.1.1有交集。
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一级分类：Mathematics        数学
二级分类：Information Theory        信息论
分类描述：math.IT is an alias for cs.IT. Covers theoretical and experimental aspects of information theory and coding.
它是cs.it的别名。涵盖信息论和编码的理论和实验方面。
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一级分类：Physics        物理学
二级分类：Biological Physics        生物物理学
分类描述：Molecular biophysics, cellular biophysics, neurological biophysics, membrane biophysics, single-molecule biophysics, ecological biophysics, quantum phenomena in biological systems (quantum biophysics), theoretical biophysics, molecular dynamics/modeling and simulation, game theory, biomechanics, bioinformatics, microorganisms, virology, evolution, biophysical methods.
分子生物物理、细胞生物物理、神经生物物理、膜生物物理、单分子生物物理、生态生物物理、生物系统中的量子现象（量子生物物理）、理论生物物理、分子动力学/建模与模拟、博弈论、生物力学、生物信息学、微生物、病毒学、进化论、生物物理方法。
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英文摘要：
  Information theory has explained the organization of many biological phenomena, from the physiology of sensory receptive fields to the variability of certain DNA sequence ensembles. Some scholars have proposed that information should provide the central explanatory principle in biology, in the sense that any behavioral strategy that is optimal for an organism's survival must necessarily involve efficient information processing. We challenge this view by providing a counterexample. We present an analytically tractable model for a particular instance of a perception-action loop: a creature searching for a food source confined to a one-dimensional ring world. The model incorporates the statistical structure of the creature's world, the effects of the creature's actions on that structure, and the creature's strategic decision process. The model takes the form of a Markov process on an infinite dimensional state space. To analyze it we construct an exact coarse graining that reduces the model to a Markov process on a finite number of "information states". This technique allows us to make quantitative comparisons between the performance of an information-theoretically optimal strategy with other candidate strategies on a food gathering task. We find that: 1. Information optimal search does not necessarily optimize utility (expected food gain). 2. The rank ordering of search strategies by information performance does not predict their ordering by expected food obtained. 3. The relative advantage of different strategies depends on the statistical structure of the environment, in particular the variability of motion of the source. We conclude that there is no simple relationship between information and utility. Behavioral optimality does not imply information efficiency, nor is there a simple tradeoff between gaining information about a food source versus obtaining the food itself.
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PDF链接：
https://arxiv.org/pdf/1010.4726