This paper studies the simulation of the Nile River as a multi-objective reinforcement learning problem. The main goal of this essay is to develop and evaluate the visualization techniques to effectively present the results of reinforcement learning models. Using a multi-objective approach, visualizations are very important for understanding the trade-offs and complexities in managing the Nile River problem.

This study includes a user evaluation to compare different visualizations, analyzing their effectiveness in terms of their clarity and usefulness using ANOVA test. Additionally, the effectiveness of clustering and full data points will be analyzed using a chi-square test to choose which visualisation technique works the best.

According to the results, stacked bar chart and parallel coordinates plot performed the best, while the spider plot performed the worst. Additionally, there is no preference between clustered and full data points visualizations based on the user evaluation.