author = "Jie Wang and Jiwei Liu and Bin Feng and Gang Hou",
booktitle = "2015 Ninth International Conference on Frontier of
Computer Science and Technology",
title = "The Dynamic Evaluation Strategy for Evolvable
Hardware",
year = "2015",
pages = "91--95",
abstract = "Evolvable hardware (EHW) has recently become a highly
attractive topic for the Fault-tolerant System design
because it offers a way of adapting hardware to
different environments. However, it is time-consuming
when circuits become complex. According to our
research, the most time consuming period in genetic
algorithm (GA) is the fitness evaluation. To reduce the
time, a new method based on fitness evaluation
expansion GA is proposed. The fitness evaluation is
divided into two stages by a threshold. When the
generation is lower than the threshold, a fitness
estimate strategy is introduced to estimate the
offspring's fitness. When really evolving the fitness,
a self-adaptive random sampling model is applied to
select the output node from the Cartesian Genetic
Programming (CGP) array. During the evolution process,
the random sampling probability can be adjusted
dynamically with the concentration degree of
individuals, which can short the evaluation time and
accelerate the convergence. Experiments show that this
method can obtain about 5 times speedup while getting
an ideal circuit.",