MUMBAI, India, June 26 -- Intellectual Property India has published a patent application (202641072784 A) filed by Lefeer Muhamed Marakkarackayil on June 12, 2026, for Adaptive Computing System For Learner-Led Aspiration Mapping Using Multidimensional Context Vectors And Closed-Loop Feedback Control.
Inventor includes Lefeer Muhamed Marakkarackayil.
The application for the patent was published on June 19, 2026, under issue no. 25/2026.
Abstract: [058] The present invention relates to an adaptive computing system for learner-led aspiration mapping using multidimensional context vectors and closed-loop feedback control. The system comprises processors, memory, learner interfaces, repositories, and computational engines including a direction engine, commitment engine, capability engine, context engine, progress engine, and recommendation and engagement engine. The direction engine converts learner aspiration into a multidimensional aspiration vector and computes direction strength. The commitment engine computes commitment from behavioral execution logs. The capability engine generates capability vectors, learning agility indicators, and aspiration gap values. The context engine generates opportunity and constraint vectors using career taxonomy, opportunity signals, and learner-specific barriers. The progress engine computes progress index, distance, effective growth rate, directional accuracy, and drift signals. The recommendation engine generates explainable pathway, goal, task, learning, career, and behavioral recommendations. An agency governance module preserves learner control by requiring acceptance, deferment, rejection, modification, or rollback before recommendation implementation. Accompanied Drawing [FIGS. 1-2]
Disclaimer: Curated by HT Syndication.
