Methods of swarm algorithms solution of applied tasks in geoinformation systems

: pp. 87 - 106
Lviv Polytechnic National University, Lviv, Ukraine
Chernivtsi Philosophical and Legal Lyceum № 2, Chernivtsi

At this article proposed to use intelligent planning agents using ontological approach to automate the procedures of formation of many alternative solutions and the choice of rational decision in branch of GIS. It proposed to use the developed knowledge base in the field of methods of swarm intelligence based on adaptive ontology and a database of scientific publications in this field. All applied problems in the branch of geoinformation systems are divided into classes of problems: stationary, quasi-stationary, dynamic. It is suggested to determine the free parameters for individual swarm algorithms based on machine learning with reinforcement, namely the Q-Learning method. On the basis of this method Markov chains for the swarm algorithms were constructed. Reinforcement consisted of the expert analysis of the results obtained by a certain swarm algorithm. On the example of territorial administration, optimal values of the parameters of individual swarm algorithms were found.

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