Abstract:
In this paper, we discuss the benefits of several fuzzy inference system
design methodologies and evaluate their characteristics in regard to our
trustworthiness and QoS measurement models. Our analysis shows that Mamdani-
Assilian or Larsen type and Takagi-Sugeno-Kang type fuzzy inference
methods have their merits in different situations. We propose to equip an
autonomous agent which acts on behalf of a human being with a policy table
enabling the agent to dynamically decide which fuzzy inference system it will
select during the trustworthiness evaluation process. We argue that in most
situations the Mamdani-Assilian or Larsen type fuzzy inference system represents
the preferred choice. However, in situations where the fuzzy rulebase is
large, the Takagi-Sugeno-Kang type fuzzy inference system should be chosen
due to its superior performance characteristics. This way the agent can perform
its tasks more efficiently by choosing the appropriate calculation method depending
on the given circumstances.
