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The Ant Colony Probabilistic Model Equivalency to the Options Uncertainty Extremized One

Репозитарій Національного Авіаційного Університету

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Title The Ant Colony Probabilistic Model Equivalency to the Options Uncertainty Extremized One
 
Creator Goncharenko, Andriy Viktorovich
 
Subject mathematical model
ant colony
economic activity
optimization
algorithm
option
probability
preference
distribution
entropy
external observer
internal active participant
330.83:52.8(045)
 
Description The discussion seems be fruitful in the interpretations of the external and internal perception of the process. For example, in the road traffic, a pedestrian may see the probabilities of the cars moves, however each of the drivers navigates his/her own car in his/her own preferences distributions way. For the drivers’ it is not a probability measure where to go, the probability of something perhaps may help him/her form the preferences of the routs although. Similar ideas are applicable to the bee swarm activity optimization theories.
It is suggested to try to find a certain plausible explanation for the principal relation of the ant colony optimization algorithm traditional probabilistic model. The model is applicable to economic activity and business modeling of objects and processes. The equivalency of the probabilistic relation to the solutions of three functionals with the entropy member for preferences functions is shown. Thus, it is proved that the traditional probabilistic model itself is optimal in some sense. The discussion section raises disputable questions about the choice probability for an external observer and optimal preferences distributions for an internal active participant of the processes. Analytical expressions are illustrated with the necessary diagrams.
 
Date 2020-06-16T14:19:09Z
2020-06-16T14:19:09Z
2020-06-16
 
Type Video
 
Identifier Goncharenko A. V. The Ant Colony Probabilistic Model Equivalency to the Options Uncertainty Extremized One [video] / A. V. Goncharenko // The 2020 10th International Conference on Advanced Computer Information Technologies. Deggendorf, GERMANY. – 16 June, 2020. – 14:30 minutes. NAU Electronic Repository.
UDC 330.83:52.8(045)
http://er.nau.edu.ua/handle/NAU/43537
 
Language en_US
 
Format application/octet-stream
application/msword
 
Publisher National Aviation University
 

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