Incorporating artificial intelligence in shopping assistance robot using Markov Decision Process

Abstract

There are many challenges involved in the realization of a shopping assistance robot (SAR). The specific challenge addressed in this paper is that of incorporating artiticial intelligence or decision making capability in such robot. Markov Decision Process (MDP) based formulation of the problem has been presented for this purpose. The major advantage of the MDP based approach over simple search based artificial intelligence techniques is that it can incorporate uncertainty. The proposed MDP model has been solved for optimal policy using value iteration algorithm. Furthermore, it has been shown how the reward function influences the structure of the resulting policy. The results show encouraging potential in the use ofMDP based formulation for SAR.

Artificial Intelligence–Based Consumer Health Informatics Application: Scoping Review

“…However, the use of AI in health care is not limited to clinical health IT applications. AI systems also have the potential to improve the patient-centeredness of health care [ 19 ] by enhancing patient health self-management tools such as smartphone apps [ 20 , 21 ], assistant robots [ 22 , 23 ], and self-monitoring devices [ 24 - 26 ], which are various types of CHI tools. It is essential to understand how patients and consumers perceive and experience the use of these technologies.…”