Using Multi-agent Systems for Sampling and Rendering Implicit Surfaces

In this paper a multi-agent system for sampling and rendering implicit surfaces is presented (MASSRIS). Previous approaches to pen-and-ink style renderings of implicit surfaces were based on particle systems, which, for a complex surface, are slow to achieve a good distribution of particles and subsequently to trace features. The method proposed in this research extends traditional particles into semi-autonomous agents that sample the implicit model and illustrate surface features. Agents use goal directed behaviors to achieve a good coverage of surface strokes and feature outline identification faster than with previous particle-based methods.