Description

Anticipation is a neuro-cognitive mechanism that enables humans to predict future events, from everyday tasks to complex actions. However, enabling machines to anticipate future actions remains challenging due to difficulties in representing and exploiting contextual knowledge. This project addresses this challenge by developing a deep learning model for future action prediction based on the MAMBA architecture, which is effective at modeling long-range dependencies.