scholarly journals Mate choice and the evolutionary stability of a fixed threshold in a sequential search strategy

2014 ◽  
Vol 10 (16) ◽  
pp. 8-11 ◽  
Author(s):  
Raymond Cheng ◽  
Steven M. Seubert ◽  
Daniel D. Wiegmann
Author(s):  
Yusuke Kubo ◽  
◽  
Masao Kubo ◽  
Hiroshi Sato ◽  
Akira Namatame

We propose a method that uses a large number of digital photographs to produce highly accurate estimates of the locations of subjects that have attracted a crowd’s attention. Recently, a very active area of research has been to use humans as sensors in realworld observations that require a large amount of data. Some of these studies have attempted to produce real-time estimates of the subjects that are attracting a crowd’s attention by quickly collecting a large number of photographs. These studies are based on the assumption that, when photographers encounter interesting events, they take pictures. Some of the proposed methods realize high availability by using only photographing information, which includes information about location and azimuth of the camera and it is automatically embedded into photograph. Since this data is very small compared to that of the pixel information, the load on the communication infrastructure is reduced. However, there are problems with the accuracy when there are many attractive subjects in a small region, and they cannot be found with traditional methods that use a sequential search strategy. The proposed method overcomes this problem by applying nonnegative matrix factorization (NMF) to the estimated location of each subject. We verified the effectiveness of this by computational experiments and an experiment under a realistic environment.


1997 ◽  
Vol 08 (01) ◽  
pp. 27-39 ◽  
Author(s):  
R. Herpers ◽  
L. Witta ◽  
J. Bruske ◽  
G. Sommer

In this contribution Dynamic Cell Structures (DCS network) are applied to classify local image structures at particular facial landmarks. The facial landmarks such as the corners of the eyes or intersections of the iris with the eyelid are computed in advance by a combined model and data driven sequential search strategy. To reduce the detection error after the processing of the sequential search strategy, the computed image positions are verified applying a DCS network. The DCS network is trained by supervised learning with feature vectors which encode spatially arranged edge and structural information at the keypoint position considered. The model driven localization as well as the data driven verification are based on steerable filters, which build a representation comparable with one provided by a receptive field in the human visual system. We apply a DCS based classifier because of its ability to grasp the topological structure of complex input spaces and because it has proved successful in a number of other classification tasks. In our experiments the average error resulting from false positive classifications is less than 1%.


2013 ◽  
Vol 59 (2) ◽  
pp. 184-199 ◽  
Author(s):  
Daniel D. Wiegmann ◽  
Lisa M. Angeloni ◽  
Steven M. Seubert ◽  
J. Gordon

Abstract For more than two decades rudimentary versions of the fixed sample and sequential search strategies have provided the primary theoretical foundation for the study of mate choice decisions by searchers. The theory that surrounds these models has expanded markedly over this time period. In this paper, we review and extend results derived from these models, with a focus on the empirical analysis of searcher behavior. The basic models are impractical for empirical purposes because they rely on the assumption that searchers—and, for applied purposes, researchers—assess prospective mates based on their quality, the fitness consequences of mate choice decisions. Here we expound versions of the models that are more empirically useful, reformulated to reflect decisions based on male phenotypic characters. For some organisms, it may be possible to use preference functions to derive predictions from the reformulated models and thereby avoid difficulties associated with the measurement of male quality per se. But predictions derived from the two models are difficult to differentiate empirically, regardless of how the models are formulated. Here we develop ideas that illustrate how this goal might be accomplished. In addition, we clarify how the variability of male quality should be evaluated and we extend what is known about how this variability influences searcher behavior under each model. More general difficulties associated with the empirical study of mate choice decisions by searchers are also discussed.


2002 ◽  
Vol 10 (2) ◽  
pp. 113-136 ◽  
Author(s):  
Jorge Simao ◽  
Peter M Todd

We present a conceptual framework for the study of mate choice in monogamous mating systems with non-negligible courtship time. Within this framework, we develop a mate choice model for the common case where individuals have a changing social network of potential partners. The performance and robustness of different agent strategies is evaluated, emphasizing the important role that courtship plays in mate choice. Specifically, the courtship period can be used by individuals to swap to better partners when they become available. We found that using courtship as a mechanism for holding partners before full commitment to mating provides strategic advantages relative to sequential search using aspiration levels. Moreover, simple heuristics that require little computation provide a degree of robustness to environmental (parameter) changes that is unattainable by strategies based on more extensive information processing. Our model produces realistic patterns of assortative mating (high within-couple mate value correlations) and rates of mating that match empirical data on human sexual/romantic relationships much more closely than previous accounts from biology and the social sciences.


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