The Experts below are selected from a list of 318 Experts worldwide ranked by ideXlab platform
Marco Tomassini - One of the best experts on this subject based on the ideXlab platform.
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PERFORMANCE AND ROBUSTNESS OF CELLULAR AUTOMATA COMPUTATION ON IRREGULAR NETWORKS
Advances in Complex Systems, 2007Co-Authors: Christian Darabos, Mario Giacobini, Marco TomassiniAbstract:We investigate the performances of Collective Task-solving capabilities and the robustness of complex networks of automata using the density and synchronization problems as typical cases. We show by computer simulations that evolved Watts–Strogatz small-world networks have superior performance with respect to several kinds of scale-free graphs. In addition, we show that Watts–Strogatz networks are as robust in the face of random perturbations, both transient and permanent, as configuration scale-free networks, while being widely superior to Barabasi–Albert networks. This result differs from information diffusion on scale-free networks, where random faults are highly tolerated by similar topologies.
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ACRI - Scale-Free automata networks are not robust in a Collective computational Task
Lecture Notes in Computer Science, 2006Co-Authors: Christian Darabos, Mario Giacobini, Marco TomassiniAbstract:We investigate the performances and Collective Task-solving capabilities of complex networks of automata using the density problem as a typical case We show by computer simulations that evolved Watts–Strogatz small-world networks have superior performance with respect to scale-free graphs of the Albert–Barabasi type Besides, Watts–Strogatz networks are much more robust in the face of transient uniformly random perturbations This result differs from information diffusion on scale-free networks, where random faults are highly tolerated.
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scale free automata networks are not robust in a Collective computational Task
Cellular Automata for Research and Industry, 2006Co-Authors: Christian Darabos, Mario Giacobini, Marco TomassiniAbstract:We investigate the performances and Collective Task-solving capabilities of complex networks of automata using the density problem as a typical case We show by computer simulations that evolved Watts–Strogatz small-world networks have superior performance with respect to scale-free graphs of the Albert–Barabasi type Besides, Watts–Strogatz networks are much more robust in the face of transient uniformly random perturbations This result differs from information diffusion on scale-free networks, where random faults are highly tolerated.
Christian Darabos - One of the best experts on this subject based on the ideXlab platform.
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PERFORMANCE AND ROBUSTNESS OF CELLULAR AUTOMATA COMPUTATION ON IRREGULAR NETWORKS
Advances in Complex Systems, 2007Co-Authors: Christian Darabos, Mario Giacobini, Marco TomassiniAbstract:We investigate the performances of Collective Task-solving capabilities and the robustness of complex networks of automata using the density and synchronization problems as typical cases. We show by computer simulations that evolved Watts–Strogatz small-world networks have superior performance with respect to several kinds of scale-free graphs. In addition, we show that Watts–Strogatz networks are as robust in the face of random perturbations, both transient and permanent, as configuration scale-free networks, while being widely superior to Barabasi–Albert networks. This result differs from information diffusion on scale-free networks, where random faults are highly tolerated by similar topologies.
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ACRI - Scale-Free automata networks are not robust in a Collective computational Task
Lecture Notes in Computer Science, 2006Co-Authors: Christian Darabos, Mario Giacobini, Marco TomassiniAbstract:We investigate the performances and Collective Task-solving capabilities of complex networks of automata using the density problem as a typical case We show by computer simulations that evolved Watts–Strogatz small-world networks have superior performance with respect to scale-free graphs of the Albert–Barabasi type Besides, Watts–Strogatz networks are much more robust in the face of transient uniformly random perturbations This result differs from information diffusion on scale-free networks, where random faults are highly tolerated.
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scale free automata networks are not robust in a Collective computational Task
Cellular Automata for Research and Industry, 2006Co-Authors: Christian Darabos, Mario Giacobini, Marco TomassiniAbstract:We investigate the performances and Collective Task-solving capabilities of complex networks of automata using the density problem as a typical case We show by computer simulations that evolved Watts–Strogatz small-world networks have superior performance with respect to scale-free graphs of the Albert–Barabasi type Besides, Watts–Strogatz networks are much more robust in the face of transient uniformly random perturbations This result differs from information diffusion on scale-free networks, where random faults are highly tolerated.
Mario Giacobini - One of the best experts on this subject based on the ideXlab platform.
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PERFORMANCE AND ROBUSTNESS OF CELLULAR AUTOMATA COMPUTATION ON IRREGULAR NETWORKS
Advances in Complex Systems, 2007Co-Authors: Christian Darabos, Mario Giacobini, Marco TomassiniAbstract:We investigate the performances of Collective Task-solving capabilities and the robustness of complex networks of automata using the density and synchronization problems as typical cases. We show by computer simulations that evolved Watts–Strogatz small-world networks have superior performance with respect to several kinds of scale-free graphs. In addition, we show that Watts–Strogatz networks are as robust in the face of random perturbations, both transient and permanent, as configuration scale-free networks, while being widely superior to Barabasi–Albert networks. This result differs from information diffusion on scale-free networks, where random faults are highly tolerated by similar topologies.
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ACRI - Scale-Free automata networks are not robust in a Collective computational Task
Lecture Notes in Computer Science, 2006Co-Authors: Christian Darabos, Mario Giacobini, Marco TomassiniAbstract:We investigate the performances and Collective Task-solving capabilities of complex networks of automata using the density problem as a typical case We show by computer simulations that evolved Watts–Strogatz small-world networks have superior performance with respect to scale-free graphs of the Albert–Barabasi type Besides, Watts–Strogatz networks are much more robust in the face of transient uniformly random perturbations This result differs from information diffusion on scale-free networks, where random faults are highly tolerated.
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scale free automata networks are not robust in a Collective computational Task
Cellular Automata for Research and Industry, 2006Co-Authors: Christian Darabos, Mario Giacobini, Marco TomassiniAbstract:We investigate the performances and Collective Task-solving capabilities of complex networks of automata using the density problem as a typical case We show by computer simulations that evolved Watts–Strogatz small-world networks have superior performance with respect to scale-free graphs of the Albert–Barabasi type Besides, Watts–Strogatz networks are much more robust in the face of transient uniformly random perturbations This result differs from information diffusion on scale-free networks, where random faults are highly tolerated.
Amos Korman - One of the best experts on this subject based on the ideXlab platform.
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Limits on reliable information flows through stochastic populations
PLoS Computational Biology, 2018Co-Authors: Lucas Boczkowski, Emanuele Natale, Ofer Feinerman, Amos KormanAbstract:Biological systems can share and Collectively process information to yield emergent effects, despite inherent noise in communication. While man-made systems often employ intricate structural solutions to overcome noise, the structure of many biological systems is more amorphous. It is not well understood how communication noise may affect the computational repertoire of such groups. To approach this question we consider the basic Collective Task of rumor spreading, in which information from few knowledgeable sources must reliably flow into the rest of the population. We study the effect of communication noise on the ability of groups that lack stable structures to efficiently solve this Task. We present an impossibility result which strongly restricts reliable rumor spreading in such groups. Namely, we prove that, in the presence of even moderate levels of noise that affect all facets of the communication , no scheme can significantly outperform the trivial one in which agents have to wait until directly interacting with the sources-a process which requires linear time in the population size. Our results imply that in order to achieve efficient rumor spread a system must exhibit either some degree of structural stability or, alternatively, some facet of the communication which is immune to noise. We then corroborate this claim by providing new analyses of experimental data regarding recruitment in Cataglyphis niger desert ants. Finally, in light of our theoretical results, we discuss strategies to overcome noise in other biological systems. Author summary Biological systems must function despite inherent noise in their communication. Systems that enjoy structural stability, such as biological neural networks, could potentially overcome noise using simple redundancy-based procedures. However, when individuals have little control over who they interact with, it is unclear what conditions would prevent runaway error accumulation. This paper takes a general stance to investigate this problem, concentrating on the basic information-dissemination Task of rumor spreading. Drawing on a theoretical model, we prove that fast rumor spreading can only be achieved if some part of the communication setting is either stable or reliable. We then provide empirical PLOS Computational Biology | https://doi.org/10.1371/journal.pcbi.
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Limits for Rumor Spreading in Stochastic Populations
2018Co-Authors: Lucas Boczkowski, Ofer Feinerman, Amos Korman, Emanuele NataleAbstract:Biological systems can share and Collectively process information to yield emergent effects , despite inherent noise in communication. While man-made systems often employ intricate structural solutions to overcome noise, the structure of many biological systems is more amorphous. It is not well understood how communication noise may affect the computational repertoire of such groups. To approach this question we consider the basic Collective Task of rumor spreading, in which information from few knowledgeable sources must reliably flow into the rest of the population. In order to study the effect of communication noise on the ability of groups that lack stable structures to efficiently solve this Task, we consider a noisy version of the uniform PU LL model. We prove a lower bound which implies that, in the presence of even moderate levels of noise that affect all facets of the communication, no scheme can significantly outperform the trivial one in which agents have to wait until directly interacting with the sources. Our results thus show an exponential separation between the uniform PU SH and PU LL communication models in the presence of noise. Such separation may be interpreted as suggesting that, in order to achieve efficient rumor spreading, a system must exhibit either some degree of structural stability or, alternatively, some facet of the communication which is immune to noise. We corroborate our theoretical findings with a new analysis of experimental data regarding recruitment in Cataglyphis niger desert ants.
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Limits on reliable information flows through stochastic populations.
Public Library of Science (PLoS), 2018Co-Authors: Lucas Boczkowski, Emanuele Natale, Ofer Feinerman, Amos KormanAbstract:Biological systems can share and Collectively process information to yield emergent effects, despite inherent noise in communication. While man-made systems often employ intricate structural solutions to overcome noise, the structure of many biological systems is more amorphous. It is not well understood how communication noise may affect the computational repertoire of such groups. To approach this question we consider the basic Collective Task of rumor spreading, in which information from few knowledgeable sources must reliably flow into the rest of the population. We study the effect of communication noise on the ability of groups that lack stable structures to efficiently solve this Task. We present an impossibility result which strongly restricts reliable rumor spreading in such groups. Namely, we prove that, in the presence of even moderate levels of noise that affect all facets of the communication, no scheme can significantly outperform the trivial one in which agents have to wait until directly interacting with the sources-a process which requires linear time in the population size. Our results imply that in order to achieve efficient rumor spread a system must exhibit either some degree of structural stability or, alternatively, some facet of the communication which is immune to noise. We then corroborate this claim by providing new analyses of experimental data regarding recruitment in Cataglyphis niger desert ants. Finally, in light of our theoretical results, we discuss strategies to overcome noise in other biological systems
Natalie A. Kerr - One of the best experts on this subject based on the ideXlab platform.
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achievement motivation expected coworker performance and Collective Task motivation working hard or hardly working 1
Journal of Applied Social Psychology, 2004Co-Authors: Jason Hart, Steven J. Karau, Marx F. Stasson, Natalie A. KerrAbstract:Social loafing is the tendency of individuals to work less hard Collectively than individually. The present study examined the joint influence of achievement motivation and expected coworker effort on Collective Task performance. Participants (N = 107) who qualified and were available after pretesting on an achievement motivation scale were randomly assigned to a work condition and coworker effort condition. Dyads were asked to generate as many uses for a knife as possible within a 12-min time period. Participants low in achievement motivation engaged in social loafing, but only when expected coworker effort was high, whereas participants high in achievement motivation did not engage in social loafing, regardless of expected coworker effort. The implication of achievement motivation for Collective Task performance settings is discussed.
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Achievement Motivation, Expected Coworker Performance, and Collective Task Motivation: Working Hard or Hardly Working?1
Journal of Applied Social Psychology, 2004Co-Authors: Jason Hart, Steven J. Karau, Marx F. Stasson, Natalie A. KerrAbstract:Social loafing is the tendency of individuals to work less hard Collectively than individually. The present study examined the joint influence of achievement motivation and expected coworker effort on Collective Task performance. Participants (N = 107) who qualified and were available after pretesting on an achievement motivation scale were randomly assigned to a work condition and coworker effort condition. Dyads were asked to generate as many uses for a knife as possible within a 12-min time period. Participants low in achievement motivation engaged in social loafing, but only when expected coworker effort was high, whereas participants high in achievement motivation did not engage in social loafing, regardless of expected coworker effort. The implication of achievement motivation for Collective Task performance settings is discussed.