VAT - A New Approach to Multi-agent Systems Visualization

D. Řehoř, D. Kadleček, P. Slavík, and P. Nahodil (Czech Republic)


Multi-agent systems, artificial life, visualization, multivariate data


Multi-agent systems analysis using advanced methods of visualization is presented. As multi-agent systems are becoming more complex and thereby harder to analyze and assess, traditional methods of MAS analysis are becoming insufficient. The main purpose of this paper is to show how new visualization techniques can greatly improve the efficiency of analysis of multi-agent systems behavior. Proposed visualization techniques have been successfully tested on Artificial Life Simulator (ALS) where agents leveraging the CZAR internal architecture were deployed.

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