Using Data-Compressors for Classification Hunting Behavioral Sequences in Rodents as “Ethological Texts”

作者: Jan Levenets , Anna Novikovskaya , Sofia Panteleeva , Zhanna Reznikova , Boris Ryabko

DOI: 10.3390/MATH8040579

关键词: Statistical hypothesis testingBehavioral patternEthologyArtificial intelligenceMathematical statisticsMachine learningData compressionAssociation (psychology)Pairwise comparisonAnimal behaviorComputer science

摘要: One of the main problems in comparative studying animal behavior is searching for an adequate mathematical method evaluating similarities and differences between behavioral patterns. This study aims to propose a new tool evaluate ethological species. We developed compression-based homogeneity testing classification investigate hunting small mammals. A distinction this approach that it belongs framework statistics allows one compare structural characteristics any texts pairwise comparisons. To validate method, we compared behaviors different species mammals as “texts.” do this, coded elements with letters. then tested hypothesis whether sequences “texts” are generated either by single source or ones. Based on association coefficients obtained from comparisons, built types behaviors, which brought unique insight into how particular rodents changed evolved. suggest relevant evolutionary analysis.

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