Arms Race

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Edmund D Brodie - One of the best experts on this subject based on the ideXlab platform.

  • phenotypic mismatches reveal escape from Arms Race coevolution
    PLOS Biology, 2008
    Co-Authors: Charles T Hanifin, Edmund D Brodie
    Abstract:

    Because coevolution takes place across a broad scale of time and space, it is virtually impossible to understand its dynamics and trajectories by studying a single pair of interacting populations at one time. Comparing populations across a range of an interaction, especially for long-lived species, can provide insight into these features of coevolution by sampling across a diverse set of conditions and histories. We used measures of prey traits (tetrodotoxin toxicity in newts) and predator traits (tetrodotoxin resistance of snakes) to assess the degree of phenotypic mismatch across the range of their coevolutionary interaction. Geographic patterns of phenotypic exaggeration were similar in prey and predators, with most phenotypically elevated localities occurring along the central Oregon coast and central California. Contrary to expectations, however, these areas of elevated traits did not coincide with the most intense coevolutionary selection. Measures of functional trait mismatch revealed that over one-third of sampled localities were so mismatched that reciprocal selection could not occur given current trait distributions. Estimates of current locality-specific interaction selection gradients confirmed this interpretation. In every case of mismatch, predators were “ahead” of prey in the Arms Race; the converse escape of prey was never observed. The emergent pattern suggests a dynamic in which interacting species experience reciprocal selection that drives Arms-Race escalation of both prey and predator phenotypes at a subset of localities across the interaction. This coadaptation proceeds until the evolution of extreme phenotypes by predators, through genes of large effect, allows snakes to, at least temporarily, escape the Arms Race.

Ronald Smith - One of the best experts on this subject based on the ideXlab platform.

  • Arms Race models and econometric applications
    2020
    Co-Authors: J. Paul Dunne, Eftychia Nikolaidou, Ronald Smith
    Abstract:

    Richardson’s action-reaction model of an Arms Race has prompted a considerable body of research which has attempted to empirically estimate such models. In general these attempts have been unsuccessful. This paper reconsiders the estimation issues using some recent developments in time-series econometrics, illustrating the issues with estimates for Greece and Turkey and India and Pakistan. Whereas there is little evidence for a Richardson type Arms Race for Greece and Turkey, India and Pakistan show a stable interaction with a well determined equilibrium.

  • The Influence of the Richardson Arms Race Model
    Pioneers in Arts Humanities Science Engineering Practice, 2019
    Co-Authors: Ronald Smith
    Abstract:

    This chapter reviews the Richardson Arms Race model: a pair of differential equations which capture an action reaction process. Whereas many of Richardson’s equations were quite specific about what they referred to, the Arms Race model was not. This lack of specificity was both a strength and a weakness. Its strength was that with different interpretations it could be applied as an organising structure in a wide variety of contexts. Its weakness was that the model could not be estimated or tested without some auxiliary interpretation. The chapter considers the impact of these issues in interpretation and empirical application on the influence of the Richardson Arms Race model.

  • Is there an Arms Race between Greece and Turkey
    Peace Economics Peace Science and Public Policy, 2005
    Co-Authors: J. Paul Dunne, Eftychia Nikolaidou, Ronald Smith
    Abstract:

    Richardson's action-reaction model of an Arms Race has prompted a considerable body of research that has attempted to empirically estimate such models. In general these attempts have been unsuccessful. This paper provides an extensive reconsideration of the estimation issues and using some recent developments in time-series econometrics, provides a comprehensive analysis of data for Greece and Turkey. It finds evidence of some form of cointegration between the military expenditures in both countries, but not of Richardson Arms Race type.

Charles T Hanifin - One of the best experts on this subject based on the ideXlab platform.

  • phenotypic mismatches reveal escape from Arms Race coevolution
    PLOS Biology, 2008
    Co-Authors: Charles T Hanifin, Edmund D Brodie
    Abstract:

    Because coevolution takes place across a broad scale of time and space, it is virtually impossible to understand its dynamics and trajectories by studying a single pair of interacting populations at one time. Comparing populations across a range of an interaction, especially for long-lived species, can provide insight into these features of coevolution by sampling across a diverse set of conditions and histories. We used measures of prey traits (tetrodotoxin toxicity in newts) and predator traits (tetrodotoxin resistance of snakes) to assess the degree of phenotypic mismatch across the range of their coevolutionary interaction. Geographic patterns of phenotypic exaggeration were similar in prey and predators, with most phenotypically elevated localities occurring along the central Oregon coast and central California. Contrary to expectations, however, these areas of elevated traits did not coincide with the most intense coevolutionary selection. Measures of functional trait mismatch revealed that over one-third of sampled localities were so mismatched that reciprocal selection could not occur given current trait distributions. Estimates of current locality-specific interaction selection gradients confirmed this interpretation. In every case of mismatch, predators were “ahead” of prey in the Arms Race; the converse escape of prey was never observed. The emergent pattern suggests a dynamic in which interacting species experience reciprocal selection that drives Arms-Race escalation of both prey and predator phenotypes at a subset of localities across the interaction. This coadaptation proceeds until the evolution of extreme phenotypes by predators, through genes of large effect, allows snakes to, at least temporarily, escape the Arms Race.

John T. Jacobs - One of the best experts on this subject based on the ideXlab platform.

  • An Artificial Arms Race: Could it Improve Mobile Malware Detectors?
    2018 Network Traffic Measurement and Analysis Conference (TMA), 2018
    Co-Authors: Rapahel Bronfman-nadas, Nur Zincir-heywood, John T. Jacobs
    Abstract:

    On the Internet today, mobile malware is one of the most common attack methods. These attacks are usually established via malicious mobile apps. To combat this threat, one technique used is the deployment of mobile malware detectors. As the mobile threats evolve, designing and developing mobile malware detectors remains a challenging task. In this paper, we aim to explore whether creating an artificial Arms Race between mobile malware and detectors could improve the ability of the detector to adapt to the evolving threats. To better model this interaction, we present a co-evolution of both sides of the Arms Race using genetic algorithms. The experimental evaluations on publicly available malicious and non-malicious mobile apps and their variants generated by the artificial Arms Race show that this approach improves the detectors understanding of the problem.

  • TMA - An Artificial Arms Race: Could it Improve Mobile Malware Detectors?
    2018 Network Traffic Measurement and Analysis Conference (TMA), 2018
    Co-Authors: Rapahel Bronfman-nadas, Nur Zincir-heywood, John T. Jacobs
    Abstract:

    On the Internet today, mobile malware is one of the most common attack methods. These attacks are usually established via malicious mobile apps. To combat this threat, one technique used is the deployment of mobile malware detectors. As the mobile threats evolve, designing and developing mobile malware detectors remains a challenging task. In this paper, we aim to explore whether creating an artificial Arms Race between mobile malware and detectors could improve the ability of the detector to adapt to the evolving threats. To better model this interaction, we present a co-evolution of both sides of the Arms Race using genetic algorithms. The experimental evaluations on publicly available malicious and non-malicious mobile apps and their variants generated by the artificial Arms Race show that this approach improves the detectors understanding of the problem.

Randall J. Swift - One of the best experts on this subject based on the ideXlab platform.

  • A stochastic Richardson's Arms Race model
    American Journal of Mathematical and Management Sciences, 2020
    Co-Authors: John Fricks, Randall J. Swift
    Abstract:

    SYNOPTIC ABSTRACTA stochastic version of the Richardson's Arms Race model is considered through the method of birth-death processes. The expected value of the model is obtained and shown to be analogous to the original deterministic Arms Race model.