This paper introduces a multiagent optimization algorithm inspired by the collective behavior of social insects. In our method, each agent encodes a possible solution of the probl...
Flying insects use highly efficient visual strategies to control their self-motion in three-dimensional space. We present a biologically inspired, minimalistic model for visual ...
Computer programming of complex systems is a time consuming effort. Results are often brittle and inflexible. Evolving, self-learning flexible multi-agent systems remain a distant ...
This paper proposes a method of visualizing and measuring evolution in Artificial Life simulations. The evolving population of agents is treated as a dynamical system. The propose...
Complexity of today's systems prevents designers from knowing everything about them and makes engineering them a difficult task for which classical engineering approaches are ...