6533b7d6fe1ef96bd1266652

RESEARCH PRODUCT

Analysis of motor control and behavior in multi agent systems by means of artificial neural networks

Thomas UthmannPeter Dauscher

subject

Self-organizing mapEngineeringMovementModels NeurologicalBiophysicsComplex systemContext (language use)Motor ActivityMachine learningcomputer.software_genreField (computer science)AnimalsHumansComputer SimulationOrthopedics and Sports MedicineDiagnosis Computer-AssistedArtificial neural networkbusiness.industryTime delay neural networkMulti-agent systemRoboticsRobotNeural Networks ComputerArtificial intelligencebusinesscomputerAlgorithms

description

Abstract This article gives a short introduction to Self-Organizing Maps, a particular form of Artificial Neural Networks and shows by some examples, how these approaches can be used in order to analyze and visualize time series data originating from complex systems. The methods shown in this article have originally been developed for the analysis of RoboCup robot soccer games, a special kind of so-called Multi Agent Systems. Although this application has no direct connection to biomechanics, the examples shown here may give an impression of the abilities of Neural Networks in the field of Time Series Analysis in general. Because of the abstractness of the methods, it appears to be very likely that they can easily be adapted to Time Series Analysis problems within the biomechanics context.

yearjournalcountryeditionlanguage
2004-04-16Clinical Biomechanics
https://doi.org/10.1016/j.clinbiomech.2004.04.007