单一信息素模型解释了先前使用两种信息素建模的蚁群觅食的经验模式

IF 2.1 3区 心理学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Cognitive Systems Research Pub Date : 2023-08-01 DOI:10.1016/j.cogsys.2023.02.005
Eric Saund , Daniel Ari Friedman
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引用次数: 0

摘要

Dussutour等人在2009年的一篇论文中提出,大头蚁(Pheidole megacephala)在觅食过程中使用两种引诱信息素:一种用于探索,另一种用于食物采集。这一说法与蚂蚁在y形迷宫中探索和采集食物的实验室研究相一致,并被认为得到了支持。作者根据蚂蚁选择不同分支的数量来测量觅食活动和群体觅食选择,实验条件改变了每个分支末端的食物可用性历史。他们建立了一个双费洛蒙数学模型来解释观察到的蚂蚁穿过左枝和右枝的速度和比例。在这里,我们表明,主要报告的实验观察可以解释由一个信息素模型。我们的研究结果表明,为了解释Dussutour等人研究的两个主要结果,假设这些蚂蚁使用两种不同的信息素是合理的,但没有必要,因此,该研究缺乏双信息素模型的决定性证据。更广泛地说,我们强调动物行为模式在感觉和认知机制方面可能是模糊的,希望能激励未来的建模工作,在不同结构的模型之间进行正式比较。
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A single-pheromone model accounts for empirical patterns of ant colony foraging previously modeled using two pheromones

In a 2009 paper, Dussutour et al. proposed that big headed ants (Pheidole megacephala) employ two attractant pheromones during foraging: one for exploration and another during food gathering. This claim was consistent with, and argued to be supported by, laboratory studies of ant exploration and food-gathering in a Y-maze apparatus. The authors measured foraging activity and colony foraging choice in terms of the number of ants choosing different branches over time, where experimental conditions modified the history of food availability at the end of each branch. They built a two-pheromone mathematical model to account for observed rates and proportions of ants traversing the left versus right branch. Here we show that the main reported experimental observations can be explained by a one-pheromone model. Our findings show that it is plausible, but unnecessary, to hypothesize that these ants employ two distinct pheromones in order to account for the two principal results of the Dussutour et al. study, and therefore, the study falls short of dispositive evidence for a two-pheromone model. More broadly, we highlight that patterns of animal behavior can be ambiguous with respect to sensory and cognitive mechanisms, hopefully motivating future modeling efforts that perform formal comparison across models with different structure.

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来源期刊
Cognitive Systems Research
Cognitive Systems Research 工程技术-计算机:人工智能
CiteScore
9.40
自引率
5.10%
发文量
40
审稿时长
>12 weeks
期刊介绍: Cognitive Systems Research is dedicated to the study of human-level cognition. As such, it welcomes papers which advance the understanding, design and applications of cognitive and intelligent systems, both natural and artificial. The journal brings together a broad community studying cognition in its many facets in vivo and in silico, across the developmental spectrum, focusing on individual capacities or on entire architectures. It aims to foster debate and integrate ideas, concepts, constructs, theories, models and techniques from across different disciplines and different perspectives on human-level cognition. The scope of interest includes the study of cognitive capacities and architectures - both brain-inspired and non-brain-inspired - and the application of cognitive systems to real-world problems as far as it offers insights relevant for the understanding of cognition. Cognitive Systems Research therefore welcomes mature and cutting-edge research approaching cognition from a systems-oriented perspective, both theoretical and empirically-informed, in the form of original manuscripts, short communications, opinion articles, systematic reviews, and topical survey articles from the fields of Cognitive Science (including Philosophy of Cognitive Science), Artificial Intelligence/Computer Science, Cognitive Robotics, Developmental Science, Psychology, and Neuroscience and Neuromorphic Engineering. Empirical studies will be considered if they are supplemented by theoretical analyses and contributions to theory development and/or computational modelling studies.
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