Emmanouil-Nektarios Kalligeris, University of Rouen Normandy, Rouen, France
Vlad Stefan Barbu, University of Rouen Normandy, Rouen, France
Guillaume Hacques, University of Rouen Normandy, Rouen, France
Ludovic Seifert, University of Rouen Normandy, Rouen, France
Nicolas Vergne, University of Rouen Normandy, Rouen, France

Abstract: This study investigates the climbing dynamics of learning on a long-time scale, by using Drifting Markov models. Climbing constitutes a complex decision-making task that requires effective visual-motor coordination and exploration of the environment. Drifting Markov models, is a class of constrained heterogeneous Markov processes that allow the modeling of data that exhibit heterogeneity. By applying the later models on real-world visual motor skill data, we aim to uncover the persistent dynamics of learning in climbing. To that end a real case study is conducted based on an experiment, with results that (a) help in the understanding of skill acquisition in physically demanding environments; and (b) provide insights into the role of exploration and visual-motor coordination in learning.

Keywords: drifting Markov models, persistent dynamics, visual-motor coordination