2017/11/14 by Andrei Olifer, Olifer, Andrei
Biochemistry, Genetics and Molecular Biology · Computer Science · #Computability, Logic, AI Algorithms #Evolutionary Algorithms and Applications #FOS: Biological sciences #Fractal and DNA sequence analysis #Quantitative Methods (q-bio.QM) #q-bio.QM
paper · pdf · doi:10.48550/arxiv.1711.05141
arxiv created 2017/11/14 · openalex publication_date 2017/11/14 · arxiv updated 2017/11/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Behavior of natural and artificial agents consists of behavioral episodes or acts. This study introduces a quantitative measure of behavioral acts -- their apparent complexity. The measure is based on the concept of the Kolmogorov complexity. It is an apparent measure because it is determined solely by the readings of the signals that directly encode percepts and actions during behavior. The article describes an algorithm of generating behavioral acts of predetermined apparent complexity. Such acts can be used to evaluate and develop learning abilities of artificial agents.