Analysis of Partial Knowledge of Correlations in an Estimation Fusion Problem

Author(s):  
Jiri Ajgl ◽  
Ondrej Straka
Author(s):  
Poppy M. Jeffries ◽  
Samantha C. Patrick ◽  
Jonathan R. Potts

AbstractMany animal populations include a diversity of personalities, and these personalities are often linked to foraging strategy. However, it is not always clear why populations should evolve to have this diversity. Indeed, optimal foraging theory typically seeks out a single optimal strategy for individuals in a population. So why do we, in fact, see a variety of strategies existing in a single population? Here, we aim to provide insight into this conundrum by modelling the particular case of foraging seabirds, that forage on patchy prey. These seabirds have only partial knowledge of their environment: they do not know exactly where the next patch will emerge, but they may have some understanding of which locations are more likely to lead to patch emergence than others. Many existing optimal foraging studies assume either complete knowledge (e.g. Marginal Value Theorem) or no knowledge (e.g. Lévy Flight Hypothesis), but here we construct a new modelling approach which incorporates partial knowledge. In our model, different foraging strategies are favoured by different birds along the bold-shy personality continuum, so we can assess the optimality of a personality type. We show that it is optimal to be shy (resp. bold) when living in a population of bold (resp. shy) birds. This observation gives a plausible mechanism behind the emergence of diverse personalities. We also show that environmental degradation is likely to favour shyer birds and cause a decrease in diversity of personality over time.


Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1440
Author(s):  
Yiran Yuan ◽  
Chenglin Wen ◽  
Yiting Qiu ◽  
Xiaohui Sun

There are three state estimation fusion methods for a class of strong nonlinear measurement systems, based on the characteristic function filter, namely the centralized filter, parallel filter, and sequential filter. Under ideal communication conditions, the centralized filter can obtain the best state estimation accuracy, and the parallel filter can simplify centralized calculation complexity and improve feasibility; in addition, the performance of the sequential filter is very close to that of the centralized filter and far better than that of the parallel filter. However, the sequential filter can tolerate non-ideal conditions, such as delay and packet loss, and the first two filters cannot operate normally online for delay and will be invalid for packet loss. The performance of the three designed fusion filters is illustrated by three typical cases, which are all better than that of the most popular Extended Kalman Filter (EKF) performance.


Automatica ◽  
2011 ◽  
Vol 47 (5) ◽  
pp. 1053-1059 ◽  
Author(s):  
Xiaojing Shen ◽  
Yunmin Zhu ◽  
Zhisheng You

2021 ◽  
pp. 000494412110374
Author(s):  
Joan Burfitt

The aim of this study was to show that some of the errors made by students when responding to mathematics assessment items can indicate progress in the development of conceptual understanding. By granting partial credit for specific incorrect responses by early secondary students, estimates of the difficulty of demonstrating full and partial knowledge of skills associated with the development of proportional reasoning were determined using Rasch analysis. The errors were confirmed as indicators of progress, and hence partial knowledge, when the thresholds of achievement followed a logical order: The greater the proficiency of the students, the more likely they were to receive a higher score. Consideration of this partial knowledge can enhance the descriptions of the likely behaviours of students at the various levels of learning progressions and this can be informative for teachers in their planning of learning activities.


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