Recommending a Fitness Assistance System Using Artificial Intelligence

Abstract

We suggest a recommender system (RS) to provide artificial intelligence support for the fitness assistance system (FAS). These recommendations are made for both new and experienced users using the RS. The objective of this project is to create an RS that can interact with humans via AI and learn, assess, predict, and provide these suggestions. The best workout for each novice has been predicted using Artificial Neural Networks and Logistic Regression. Additionally, it was created utilising the Soar architecture's reinforcement learning capabilities to aid users in choosing the right workout for them. The effectiveness of utility application is verified by the experimental results.