Cooperative multi-agent systems (MAS) are ones in which several agents attempt, through
their interaction, to jointly solve tasks or to maximize utility. Due to the interactions among the …

In the last 20 years, evolutionary algorithms (EAs) have shown to be an effective method to
solve multiobjective optimization problems (MOPs). Due to their population-based nature …

In evolutionary computation, the fitness function normally measures progress toward an
objective in the search space, effectively acting as an objective function. Through deception …

How is it possible to think new thoughts? What is creativity and can science explain it? And
just how did Coleridge dream up the creatures of The Ancient Mariner? When The Creative …

Evolutionary Robotics is a method for automatically generating artificial brains and
morphologies of autonomous robots. This approach is useful both for investigating the …

We consider “competitive coevolution,” in which fitness is based on direct competition
among individuals selected from two independently evolving populations of “hosts” and …

Although the significance of relational ties with supply chain partners to firms' operations
management has been frequently studied, it is unclear how political ties, which represent …

This paper surveys fitness functions used in the field of evolutionary robotics (ER).
Evolutionary robotics is a field of research that applies artificial evolution to generate control …

Coevolutionary algorithms behave in very complicated, often quite counterintuitive ways.
Researchers and practitioners have yet to understand why this might be the case, how to …

By synthesizing a growing body ofwork in search processes that are not driven by explicit
objectives, this paper advances the hypothesis that there is a fundamental problem with the …