Some telecommunication systems can not afford the cost of repeating a corrupted message. Instead, the message should be somewhat “corrected” by the receiver. In these cases a...
Evolutionary testing is an effective technique for automatically generating good quality test data. However, for structural testing, the technique degenerates to random testing i...
Abstract. It is an unconventional computation approach to evolve solutions instead of calculating them. Although using evolutionary computation in computer science dates back to th...
Abstract. We present a method to generate glyphs which convey complex information in graphical form. A glyph has a linear geometry which is specified using geometric operations, e...
Greg Pintilie, Brigitte Tuekam, Christopher W. V. ...
This paper introduces Dafo, a new multi-agent framework for evolutionary optimization relying on a competitive coevolutionary genetic algorithm, aka LCGA (Loosely Coupled Genetic A...
Abstract. Due to the lot of different Genetic Algorithm variants, encodings, and attacked problems, very little general theory is available to explain the internal functioning of ...
In this paper, a multi-objective genetic algorithm is proposed to deal with a real-world fuzzy job shop scheduling problem. Fuzzy sets are used to model uncertain due dates and pro...
We use case-injected genetic algorithms for learning how to competently play computer strategy games. Case-injected genetic algorithms combine genetic algorithm search with a case-...
The tagging problem in natural language processing is to find a way to label every word in a text as a particular part of speech, e.g., proper noun. An effective way of solving th...
The problem attempted in this paper is to select a sample from a large set where the sample is required to have a particular average property. The problem can be expressed as an o...