Evolving Diverse Hardwares Using Speciated Genetic Algorithm

نویسندگان

  • Keum-Sung Hwang
  • Sung-Bae Cho
چکیده

Evolvable Hardware (EHW) is an attractive topic recently because it can reconfigure itself to adapt to the environment embedded. An EHW uses genetic algorithm, one of evolutionary algorithms to search the goal hardware. In this paper, we propose an EHW using speciated GA that can evolve diverse circuits with one-step evolution. Speciation algorithm helps finding diverse solutions as the result of the evolution and keeps the diversity during the evolution. We have applied fitness sharing method for speciation, to the EHW of 6multiplexer, and have got diverse hardware structures. Also, we have found the circuit with 35% earlier generation than conventional genetic algorithm.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Exploiting Diversity of Neural Ensembles with Speciated Evolution

In this paper, we evolve artificial neural networks (ANNs) with speciation and combine them with several methods. In general, an evolving system produces one optimal solution for a given problem. However, we argue that many other solutions exist in the final population, which can improve the overall performance. We propose a new method of evolving multiple speciated neural networks by fitness s...

متن کامل

Checkers Strategy Evolution with Speciated Neural Networks

Checkers is a very simple game and easy to learn. Unlike chess, it is simple to move and needs a few rules. With respect to checkers, the evolutionary algorithm can discover a neural network that can be used to play at a near-expert level without injecting expert knowledge about how to play the game. Evolutionary approach does not need any prior knowledge to develop machine player but can devel...

متن کامل

Speciated Neural Networks Evolved with Fitness Sharing Technique*

In order to develop effective evolutionary artificial neural networks (EANNs) we have to address the questions on how to evolve EANNs more efficiently and how to achieve the best performance from the ANNs evolved. Most of the previous works, however, do not utilize all the information obtained with several ANNs but choose the one best network in the last generation. Some recent works indicate t...

متن کامل

Evolving Non-Dominated Parameter Sets for Computational Models from Multiple Experiments

Creating robust, reproducible and optimal computational models is a key challenge for theorists in many sciences. Psychology and cognitive science face particular challenges as large amounts of data are collected and many models are not amenable to analytical techniques for calculating parameter sets. Particular problems are to locate the full range of acceptable model parameters for a given da...

متن کامل

DNA Gene Expression Classification with Ensemble Classifiers Optimized by Speciated Genetic Algorithm

Accurate cancer classification is very important to cancer diagnosis and treatment. As molecular information is increasing for the cancer classification, a lot of techniques have been proposed and utilized to classify and predict the cancers from gene expression profiles. In this paper, we propose a method based on speciated evolution for the cancer classification. The optimal combination among...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2002