Understanding Plant Movement: From Kinematics to Machine Learning

Despite their seemingly immobile nature, plants can move, a fact that has often gone overlooked. Recent discoveries have begun to furnish compelling evidence that plants are not passive organisms. They are capable of harboring intentions and translating them into goal-directed actions. This emerging evidence has sparked a lively discussion regarding the cognitive potential of plants. One innovative perspective for the study of plant behavior lies in examining it through the theoretical framework of motor cognition, which posits that cognition is fundamentally intertwined with action. My thesis is focused on investigating motor cognition in plant behavior through a combination of kinematic analysis and machine learning techniques. In particular, I dedicated myself to understanding decision-making, which entails the evaluation of costs and benefits associated with actions carried out under different contexts.