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Modelling a Common Cognitive Bias and a Simple Heuristic to Overcome it 常见认知偏差的建模和克服它的简单启发式
Pub Date : 1900-01-01 DOI: 10.1162/isal_a_00508
Michael Vogrin, Guilherme Wood, T. Schmickl
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引用次数: 0
Bottom-up formation of number representation and top-down understanding of symbolic manipulation 数字表示的自下而上的形成和符号操作的自上而下的理解
Pub Date : 1900-01-01 DOI: 10.1162/isal_a_00535
Yasuhiro Shimada, Wataru Noguchi, H. Iizuka, Masahito Yamamoto
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引用次数: 0
The evolution of adaptive phenotypic plasticity stabilizes populations against environmental fluctuations 适应性表型可塑性的进化稳定了种群免受环境波动的影响
Pub Date : 1900-01-01 DOI: 10.1162/isal_a_00499
Alexander Lalejini, Austin J. Ferguson, Nkrumah A. Grant, C. Ofria
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引用次数: 0
Self-recognition as Optimisation 自我认可为优化
Pub Date : 1900-01-01 DOI: 10.1162/isal_a_00546
Timothy James Atkinson, N. E. Toklu
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引用次数: 0
Q-learning for real time control of heterogeneous microagent collectives 基于q学习的异构微agent群实时控制
Pub Date : 1900-01-01 DOI: 10.1162/isal_a_00497
Ana Rubio Denniss, Laia Freixas Mateu, T. Gorochowski, S. Hauert
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引用次数: 1
The 2022 Conference on Artificial Life (full proceedings PDF) 2022年人工生命会议(完整会议记录PDF)
Pub Date : 1900-01-01 DOI: 10.1162/isal_a_00557
Silvia Holler, Richard J. G. Löffler, Stuart Bartlett
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引用次数: 0
Paths in a Network of Polydisperse Spherical Droplets 多分散球形液滴网络中的路径
Pub Date : 1900-01-01 DOI: 10.1162/isal_a_00502
Johann Schneider, A. Faggian, Silvia Holler, F. Casiraghi, Jin Li, Lorena Cebolla Sanahuja, H. Matuttis, M. Hanczyc, D. Barrow, M. Weyland, Dandolo Flumini, P. E. Hotz, Patrik Eschle, Aitor Patiño Diaz, R. Füchslin
We simulate the movement and agglomeration of oil droplets in water under constraints, like confinement, using a simpli-fied stochastic-hydrodynamic model. In the analysis of the network created by the droplets in the agglomeration, we focus on the paths between pairs of droplets and compare the computational results for various system sizes
我们用一个简化的随机流体动力学模型模拟了油滴在约束条件下的运动和聚集。在分析液滴在团聚中形成的网络时,我们重点关注液滴对之间的路径,并比较了不同系统尺寸的计算结果
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引用次数: 0
A Modeling and Experimental Framework for Understanding Evolutionary and Ecological Roles of Acoustic Behavior Using a Generative Model 使用生成模型理解声学行为的进化和生态作用的建模和实验框架
Pub Date : 1900-01-01 DOI: 10.1162/isal_a_00542
Reiji Suzuki, Shinji Sumitani, Chihiro Ikeda, Takaya Arita
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引用次数: 1
Perpetual Crossers without Sensory Delay: Revisiting the Perceptual Crossing Simulation Studies 无感觉延迟的永久交叉:再看知觉交叉模拟研究
Pub Date : 1900-01-01 DOI: 10.1162/isal_a_00509
E. Izquierdo, Gabriel J. Severino, Haily Merritt
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引用次数: 1
Exploiting Intrinsic Multi-Agent Heterogeneity for Spatial Interference Reduction in an Idealised Foraging Task 利用多智能体的内在异质性减少理想觅食任务中的空间干扰
Pub Date : 1900-01-01 DOI: 10.1162/isal_a_00522
C. Bennett, J. Lawry, S. Bullock
Typically, collective behaviour research has tended to focus on behaviour arising in populations of homogeneous agents. However, humans, animals, robots and software agents typically exhibit various forms of heterogeneity . In natural systems, this heterogeneity has often been associated with improved performance. In this work, we ask whether spatial interference within a population of co-operating mobile agents can be managed effectively via conflict resolution mechanisms that exploit the population’s intrinsic heterogeneity. An idealised model of foraging is presented in which a population of simulated ant-like agents is tasked with making as many journeys as possible back and forth along a route that includes tunnels that are wide enough for only one agent. Four conflict resolution schemes are used for determining which agent has priority when two or more meet within a tunnel. These schemes are tested in the context of heterogeneous populations of varying size. The findings demonstrate that a conflict resolution mechanism that exploits agent heterogeneity can achieve a significant reduction in the impact of spatial interference. However, whether or not a particular scheme is successful depends on how the heterogeneity that it exploits is implicated in the population-wide dynamics that underpin system-level performance.
通常,集体行为研究倾向于关注同质主体群体中产生的行为。然而,人类、动物、机器人和软件代理通常表现出各种形式的异质性。在自然系统中,这种异质性通常与性能的提高有关。在这项工作中,我们询问是否可以通过利用人口内在异质性的冲突解决机制有效地管理合作移动代理群体中的空间干扰。提出了一种理想的觅食模型,在这种模型中,一群模拟的类蚂蚁智能体的任务是沿着一条路线进行尽可能多的往返旅行,这条路线包括只允许一个智能体通行的隧道。当两个或多个代理在隧道内相遇时,使用了四种冲突解决方案来确定哪个代理具有优先级。这些方案在不同大小的异质种群的背景下进行了测试。研究结果表明,利用代理异质性的冲突解决机制可以显著降低空间干扰的影响。然而,一个特定方案是否成功取决于它所利用的异质性如何与支撑系统级性能的人口范围动态有关。
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引用次数: 1
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The 2022 Conference on Artificial Life
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