Evolution of integrated causal structures in animats exposed to environments of increasing complexity.
Evolution of integrated causal structures in animats exposed to environments of increasing complexity.
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DOI：
10.1371/journal.pcbi.1003966
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发表时间：
2014-12
影响因子：
4.3
通讯作者：
Tononi G
中科院分区：
文献类型：
--
作者：
Albantakis L;Hintze A;Koch C;Adami C;Tononi G
自然选择有利于大脑的进化，这些大脑可以捕捉环境因果结构中与适应性相关的特征。我们研究了小型自适应逻辑门网络（“动画”）在任务环境中的演变，其中不同大小的掉落块必须在“俄罗斯方块”游戏中被捕获或避免。解决这些任务需要集成传感器输入和存储器。进化的网络进行了评估，使用的信息集成的措施，包括进化的概念的数量和综合概念信息的总量。结果表明，在动物的适应过程中，i）概念的数量增加; ii）整合的概念信息增加; iii）这种增加依赖于环境的复杂性，特别是对顺序记忆的要求。这些结果表明，在有限的传感器和内部机制的情况下，捕捉丰富环境的因果结构的需要是生物体发展具有许多概念的高度集成网络（“大脑”）的重要驱动力，从而导致其内部复杂性的增加。整合信息的能力是生物大脑的一个突出特征，与认知灵活性和意识有关。为了研究环境复杂性如何影响信息整合能力，我们模拟了由小型自适应神经元网络（“大脑”）控制的人工生物（“动物”）的进化。任务环境的难度各不相同，主要是由于对内部存储器的要求。通过应用信息整合的措施，我们表明，在可用的内部元素的数量的限制下，animats进化的大脑，更集成的内部记忆需要解决一个给定的任务。因此，在对情境敏感性和记忆力要求较高的复杂环境中，整合的大脑结构比模块化的大脑结构具有进化优势。
Natural selection favors the evolution of brains that can capture fitness-relevant features of the environment's causal structure. We investigated the evolution of small, adaptive logic-gate networks (“animats”) in task environments where falling blocks of different sizes have to be caught or avoided in a ‘Tetris-like’ game. Solving these tasks requires the integration of sensor inputs and memory. Evolved networks were evaluated using measures of information integration, including the number of evolved concepts and the total amount of integrated conceptual information. The results show that, over the course of the animats' adaptation, i) the number of concepts grows; ii) integrated conceptual information increases; iii) this increase depends on the complexity of the environment, especially on the requirement for sequential memory. These results suggest that the need to capture the causal structure of a rich environment, given limited sensors and internal mechanisms, is an important driving force for organisms to develop highly integrated networks (“brains”) with many concepts, leading to an increase in their internal complexity. The capacity to integrate information is a prominent feature of biological brains and has been related to cognitive flexibility as well as consciousness. To investigate how environment complexity affects the capacity for information integration, we simulated the evolution of artificial organisms (“animats”) controlled by small, adaptive neuron-like networks (“brains”). Task environments varied in difficulty due primarily to the requirements for internal memory. By applying measures of information integration, we show that, under constraints on the number of available internal elements, the animats evolved brains that were the more integrated the more internal memory was required to solve a given task. Thus, in complex environments with a premium on context-sensitivity and memory, integrated brain architectures have an evolutionary advantage over modular ones.
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影响因子：
1.7
作者：
Jablonka, E
通讯作者：
Jablonka, E
影响因子：
3.3
作者：
Kashtan, Nadav;Parter, Merav;Alon, Uri
通讯作者：
Alon, Uri
影响因子：
4.3
作者：
Edlund JA;Chaumont N;Hintze A;Koch C;Tononi G;Adami C
通讯作者：
Adami C
DOI：
10.1073/pnas.231499798
发表时间：
2001-11-20
影响因子：
11.1
作者：
Edelman, GM;Gally, JA
通讯作者：
Gally, JA
DOI：
10.1111/j.1749-6632.2011.06422.x
发表时间：
2012-01-01
期刊：
YEAR IN EVOLUTIONARY BIOLOGY
影响因子：
--
作者：
Adami, Christoph
通讯作者：
Adami, Christoph