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A Casebased Strategy for Solution Synthesis among Cooperative Expert Systems
A Casebased Strategy for Solution Synthesis among
Co op erative Exp ert Systems
Minjie Zhang
Scho ol of Computer Information and Mathematical Sciences
Edith Cowan University WA Australia
mzhangcowaneduau
Abstract Most synthesis strategies for solution synthesis in distributed
exp ert systems DESs are develop ed based on analytic metho ds or in
ductive metho ds A synthesis strategy presented in this pap er is devel
op ed by casebased reasoning based on an analogical metho d In this
pap er the basic frame work of the strategy is intro duced and prelimi
nary results are demonstrated Furthermore this strategy is compared
with related work
Intro duction
Synthesis of solutions has b een b ecome one of critical issues among co op erative
exp ert systems for more than ten years Some synthesis strategies have b een
develop ed in distributed exp ert systems DESs such as These strategies
were mainly based on the mathematical analysis of the characteristics of the
inputs multiple solutions from ESs In recent years we have develop ed some
synthesis strategies using neural networks These strategies were based on a
numb er of samples with b oth inputs and corresp onding outputs nal solutions
after synthesizing corresp onding input Such samples are called p atterns
In current literature there are two metho dologies used for designing synthesis
strategies to solve synthesis problems They are analytic metho ds and inductive
metho ds An analytic metho d is a metho dology which can b e used to dene
a synthesis strategy from inputs to outputs by analyzing the characteristics of
input These characteristics may include relationships among ori
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