Design and Implementation of an Intelli-gent Painting Assistant System integrating Reinforcement Learning, Assisting Artists to Improve Creative Efficiency and Crea-tive Level

Abstract

Advanced technologies have entered the artistic processes and opened up new avenues of transformational innovations in the field of digital art. To this effect, they designed and implemented an Intelligent Painting Assistant System (IPAS) that utilized reinforcement learning to help artists improve their creative efficiency and beauty of artistic expression. A broad evaluation of the impact of the IPAS on artistic practice is carried out through user studies, simulation, and statistical analysis at several dimensions-labor efficiency, especially speed in painting, resource utilization, and creative efficiency. Substantial increases in painting speed and creative efficiency were realized among artists utilizing the IPAS. The present study will demonstrate the efficiency, speed and stability of reinforcement learning algorithms in the IPAS. It is also focused on how the IPAS can facilitate continuous learning and creativity within the creative community.