Aspects Of Evolutionary Computation Research Articles

An Efficient Genetic Encoding Scheme for Multiplierless Color Space Converter Design

Color space conversion has become a very important role in image and video processing systems. To speed up some processing processes, many communication and multimedia video compression schemes use luminance-chrominance type color spaces, such as YCbCr or YUV, making a mechanism for converting between different formats necessary. Therefore, techniques which efficiently implement this conversion are desired. For the recent years, a new field of research called Evolvable Hardware (EHW) has emerged which combines aspects of evolutionary computation with hardware design and synthesis. It is a new scheme inspired by natural evolution, for automatic design of hardware systems. This paper presents a novel evolutionary approach for efficient implementation of a RGB to YCbCr color space converter suitable for Field Programmable Gate Array (FPGAs) and VLSI. In the proposed method, we use the genetic algorithm to automatically evolve the multiplierless architecture of the color space converter. The architecture employs only a few shift and addition operations to replace the complex multiplications. The experimental results represent that the performance of implemented architecture is good at RGB to YCbCr color space converting, and it also has the advantages of high-speed, low-complexity, and low-area.

Suitability of genetic based exploration in the creative design process

Finding creative solutions to design problems depends heavily on a fruitful exploration in early phases. Many aspects of evolutionary computation (EC) and in particular genetic algorithms (GA) make them highly suited as computational tools for discovering good solutions. This paper discusses specific aspects of the GA method which parallel traditional design methodologies described by creativity researchers including Gordon, deBono, Parnes, and Osborn among others. Because EC methods work with populations of ‘fairly good’ solutions, there is less danger that creativity will be harmed by design fixation, on one ‘best’ solution. An example application is demonstrated using the design of a small truss bridge. The solutions offered by the application are varied enough to allow the designer a choice of forms. At the same time, all of the solutions offered are ‘fairly good’. This demonstrates the aspects of EC which make it well suited for creative exploration of problems.

Conference Report

GECCO-99 STUDENT WORKSHOP(13th July, 1999)The Genetic and Evolutionary Computation Conference (GECCO-99) in Orlando, Florida, USA was the biggest ever conference on evolutionary computation. It was a joint meeting of the long standing biannual International Conference on Genetic Algorithms (ICGA) which has been running since 1985 and the more recent annual Genetic Programming (GP) conference (which started in 1996). Before the start of each GP conference there has been a workshop for PhD students research in GP. This year Dr. O'Reilly (MIT AI lab) organized a joint graduate student workshop for research students principally concerned with any aspect of evolutionary computation, Evolvable Hardware, DNA computation, Artificial Life or Agents.