A Bayesian approach to the evolution of perceptual and cognitive systems
A Bayesian approach to the evolution of perceptual and cognitive systems
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DOI：
10.1016/s0364-0213(03)00009-0
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发表时间：
2003-05-01
影响因子：
2.5
通讯作者：
Diehl, RL
中科院分区：
文献类型：
--
作者：
Geisler, WS;Diehl, RL
我们描述了一个正式的框架，用于分析自然环境的统计特性和自然选择的过程如何相互作用，以确定感知和认知系统的设计。该框架由两部分组成：一个贝叶斯理想的观察者与效用函数适合自然选择，和贝叶斯制定的达尔文的自然选择理论。贝叶斯自然选择的模拟被发现产生新的见解，例如，伪装，色觉和决策标准的共同进化。贝叶斯框架以正式的方式捕捉和概括了感知和认知的其他方法的许多重要思想。(C)2003年认知科学学会All rights reserved.
We describe a formal framework for analyzing how statistical properties of natural environments and the process of natural selection interact to determine the design of perceptual and cognitive systems. The framework consists of two parts: a Bayesian ideal observer with a utility function appropriate for natural selection, and a Bayesian formulation of Darwin's theory of natural selection. Simulations of Bayesian natural selection were found to yield new insights, for example, into the co-evolution of camouflage, color vision, and decision criteria. The Bayesian framework captures and generalizes, in a formal way, many of the important ideas of other approaches to perception and cognition. (C) 2003 Cognitive Science Society, Inc. All rights reserved.