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Free, publicly-accessible full text available June 1, 2023
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We study the problem of house-hunting in ant colonies, where ants reach consensus on a new nest and relocate their colony to that nest, from a distributed computing perspective. We propose a house-hunting algorithm that is biologically inspired by Temnothorax ants. Each ant is modeled as a probabilistic agent with limited power, and there is no central control governing the ants. We show an O( log n) lower bound on the running time of our proposed house-hunting algorithm, where n is the number of ants. Furthermore, we show a matching upper bound of expected O( log n) rounds for environmentsmore »Free, publicly-accessible full text available January 1, 2023
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The Power of Population Effect in Temnothorax Ants House-Hunting: A Computational Modeling Approach.The decentralized cognition of animal groups is both a challenging biological problem and a potential basis for bio-inspired design. In this study, we investigated the house-hunting algorithm used by emigrating colonies of Temnothorax ants to reach consensus on a new nest. We developed a tractable model that encodes accurate individual behavior rules, and estimated our parameter values by matching simulated behaviors with observed ones on both the individual and group levels. We then used our model to explore a potential, but yet untested, component of the ants’ decision algorithm. Specifically, we examined the hypothesis that incorporating site population (the numbermore »Free, publicly-accessible full text available January 1, 2023
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Abstract A recent focus of quantum spin liquid (QSL) studies is how disorder/randomness in a QSL candidate affects its true magnetic ground state. The ultimate question is whether the QSL survives disorder or the disorder leads to a “spin-liquid-like” state, such as the proposed random-singlet (RS) state. Since disorder is a standard feature of most QSL candidates, this question represents a major challenge for QSL candidates. YbMgGaO 4 , a triangular lattice antiferromagnet with effective spin-1/2 Yb 3+ ions, is an ideal system to address this question, since it shows no long-range magnetic ordering with Mg/Ga site disorder. Despite themore »Free, publicly-accessible full text available December 1, 2022
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We study the problem of house-hunting in ant colonies, where ants reach consensus on a new nest and relocate their colony to that nest, from a distributed computing perspective. We propose a house-hunting algorithm that is biologically inspired by Temnothorax ants. Each ant is modelled as a probabilistic agent with limited power, and there is no central control governing the ants. We show a (log n) lower bound on the running time of our proposed house-hunting algorithm, where n is the number of ants. Further, we show a matching upper bound of expected O(log n) rounds for environments with onlymore »
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The decentralized cognition of animal groups is both a challenging biological problem and a potential basis for bio-inspired design. The understanding of these systems and their application can benefit from modeling and analysis of the underlying algorithms. In this study, we define a modeling framework that can be used to formally represent all components of such algorithms. As an example application of the framework, we adapt to it the much-studied house-hunting algorithm used by emigrating colonies of Temnothorax ants to reach consensus on a new nest. We provide a Python simulator that encodes accurate individual behavior rules and produces simulatedmore »
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We investigate the importance of quorum sensing in the success of house-hunting of emigrating Temnothorax ant colonies. Specifically, we show that the absence of the quorum sensing mechanism leads to failure of consensus during emigrations. We tackle this problem through the lens of distributed computing by viewing it as a natural distributed consensus algorithm. We develop an agent-based model of the house-hunting process, and use mathematical tools such as conditional probability, concentration bounds and Markov mixing time to rigorously prove the negative impact of not employing the quorum sensing mechanism on emigration outcomes. Our main result is a high probabilitymore »
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We study the problem of house-hunting in ant colonies, where ants reach consensus on a new nest and relocate their colony to that nest, from a distributed computing perspective. We propose a house-hunting algorithm that is biologically inspired by Temnothorax ants. Each ant is modelled as a probabilistic agent with limited power, and there is no central control governing the ants. We show a Ω(log n) lower bound on the running time of our proposed house-hunting algorithm, where n is the number of ants. Further, we show a matching upper bound of expected O(log n) rounds for environments with onlymore »