Priority Experience Replay DQN for Training an Agent in Virtual Reality Game for Kids with Paraplegia

Abstract

Virtual reality and artificial intelligence (AI) application in healthcare has shown promise in improving the lives of those with physical limitations. This article describes how an AI agent was created and then taught using the deep reinforcement learning Deep Q-Learning Network (DQN) algorithm in a virtual reality game for paraplegic children. Depending on the child's individual skills and development, the AI agent in the Virtual Reality(VR) game may provide them with feedback that is specifically suited. If the child observes actual growth over time, this might help to foster confidence and self-esteem. The AI agent may also provide real-time feedback that is responsive to the child's movements, which will help to improve the child's physical function and all-around wellbeing. Many Research have shown how AI-assisted game therapy can improve the motor skills and general wellbeing of paraplegic youngsters. In one such study, children who participated in a Virtual Reality (VR) gaming therapy created by an Artificial Intelligence (AI) agent showed remarkably greater improvements in balance and gait than those who received conventional physical therapy. In order to improve the quality of life for children with paraplegia, this research aims to use an AI agent that has been trained using the Deep Q-Learning Network(DQN) algorithm in a Virtual Reality (VR) game, that should be anticipate seeing much more varied applications of AI and VR in healthcare and treatment as technology advances.