An Interactive Visualization of Genetic Algorithm on 2-D Graph Humera Farooq Computer Science Department Future University Khartoum, Sudan Email: humera@fusudan.net Nordin Zakaria HPC Service Center, Universiti Teknologi PETRONAS, 31750,Sri Iskandar, Perak, Malaysia nordinzakaria@gmail.com Muhammad Tariq Siddique Computer Science Department Future University Khartoum, Sudan Email: tariq@fusudan.net Abstract The visualization of search space makes it easy to understand the behavior of the Genetic Algorithm (GA). We proposed a novel way for representation of multidimensional search space of the GA using 2-D graph. This visualization is carried out based on the gene values of the current generation, and human intervention is only required after several generations. The main contribution of this research is to propose an approach to visualize the GA search data and to improve the searching process of the GA with human's intention in different generations. Besides the selection of best individual or parents for the next generation, interference of human is required to propose a new individual in the search space. Hence, the active human intervention leads to a faster searching, resulting in less user fatigue. The experiments were carried out by evolving the parameters to derive the rules for a Parametric L-System. These rules are then used to model the growth process of branching structures in 3-D space. The experiments were conducted to evaluate the ability of the proposed approach to converge to optimized solution as compared to the Simple Genetic Algorithm (SGA). Keywords: Genetic Algorithm, Visualization, Human Computer Interaction, 2-D Graph, Cognitive Informatics. 1. Introduction Cognitive science is an interdisciplinary field that involves the study of human thinking and methods to solve scientific problems. It is consists of several research fields, for example medicine, phycology, education and artificial intelligence. Among these fields