Typical applications of evolutionary optimization in static environments involve the approximation of the extrema of functions. For dynamic environments, the interest is not to lo...
Learning Deterministic Finite Automata (DFA) is a hard task that has been much studied within machine learning and evolutionary computation research. This paper presents a new met...
For a mobile robot to move in a known environment and operate successfully, first it needs to robustly determine its initial position and orientation relative to the map, and then ...
Ali R. Vahdat, Naser NourAshrafoddin, Saeed Shiry ...
Many classification algorithms use the concept of distance or similarity between patterns. Previous work has shown that it is advantageous to optimize general Euclidean distances (...
Abstract--Assuming that evolutionary multiobjective optimization (EMO) mainly deals with set problems, one can identify three core questions in this area of research: (i) how to fo...