57,426 research outputs found
Evolutionary intelligent agents for e-commerce: Generic preference detection with feature analysis
Product recommendation and preference tracking systems have been adopted extensively in e-commerce businesses. However, the heterogeneity of product attributes results in undesired impediment for an efficient yet personalized e-commerce product brokering. Amid the assortment of product attributes, there are some intrinsic generic attributes having significant relation to a customer’s generic preference. This paper proposes a novel approach in the detection of generic product attributes through feature analysis. The objective is to provide an insight to the understanding of customers’ generic preference. Furthermore, a genetic algorithm is used to find the suitable feature weight set, hence reducing the rate of misclassification. A prototype has been implemented and the experimental results are promising
PACMAS: A Personalized, Adaptive, and Cooperative MultiAgent System Architecture
In this paper, a generic architecture, designed to
support the implementation of applications aimed at managing
information among different and heterogeneous sources,
is presented. Information is filtered and organized according
to personal interests explicitly stated by the user. User pro-
files are improved and refined throughout time by suitable
adaptation techniques. The overall architecture has been called
PACMAS, being a support for implementing Personalized, Adaptive,
and Cooperative MultiAgent Systems. PACMAS agents are
autonomous and flexible, and can be made personal, adaptive and
cooperative, depending on the given application. The peculiarities
of the architecture are highlighted by illustrating three relevant
case studies focused on giving a support to undergraduate and
graduate students, on predicting protein secondary structure, and
on classifying newspaper articles, respectively
Organization of Multi-Agent Systems: An Overview
In complex, open, and heterogeneous environments, agents must be able to
reorganize towards the most appropriate organizations to adapt unpredictable
environment changes within Multi-Agent Systems (MAS). Types of reorganization
can be seen from two different levels. The individual agents level
(micro-level) in which an agent changes its behaviors and interactions with
other agents to adapt its local environment. And the organizational level
(macro-level) in which the whole system changes it structure by adding or
removing agents. This chapter is dedicated to overview different aspects of
what is called MAS Organization including its motivations, paradigms, models,
and techniques adopted for statically or dynamically organizing agents in MAS.Comment: 12 page
Applied Computational Intelligence for finance and economics
This article introduces some relevant research works on computational intelligence applied to finance and economics. The objective is to offer an appropriate context and a starting point for those who are new to computational intelligence in finance and economics and to give an overview of the most recent works. A classification with five different main areas is presented. Those areas are related with different applications of the most modern computational intelligence techniques showing a new perspective for approaching finance and economics problems. Each research area is described with several works and applications. Finally, a review of the research works selected for this special issue is given.Publicad
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