Evolving User Interfaces: A Neuroevolution Approach for Natural Human-Machine Interaction

Intelligent user interfaces for human-machine interaction should be intuitive, invisible, and embodied in the user's natural physical environment. Despite recent advances, most computing systems still lack interfaces that can perceive complex visual and auditory stimuli.In this study, we propose a neuroevolution approach, employing artificial neural networks optimized by evolutionary algorithms to evolve and accurately translate user inputs into system commands. This methodology adapts and refines system responses by evolving to accommodate diverse user inputs into precise system commands.Our findings confirm the effectiveness of this approach, particularly in scenarios involving high-dimensional input spaces. The evolving interfaces developed herein show potential for improved user experiences and could pave the way for intelligent systems with natural user interfaces that understand and respond to user needs effectively.The successful application of neuroevolution methods underscores their utility in creating natural, intuitive, and personalized interfaces. The study illustrates the potential of such approaches to revolutionize human-computer interaction by allowing organic and unobtrusive interfaces that adapt to individual user behaviors and preferences.