The next generation of Collaborative Robots (Cobots) should infer the intentions of its co-workers, make rapid decisions about the best actions to execute, and learn the correct associated control strategies to achieve the desired goal without compromising the collaboration. Thus, Cobots need to have a high-level reasoning model to resemble human cognitive modeling, and a low-level control model to execute optimal skills. The synthesis of high-level reasoning with adequate low-level controls is very challenging and it is an unexplored territory that will open up new opportunities in different research areas within the Human-Robot Collaboration (HRC) field. This project aims to expand the scientific understanding of the requirements to provide a holistic solution from interpreting the collaborator’s intentions to executing the optimal robot skill autonomously, leading to better HRC.