The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper, a tool that uses an argumentation based decision making framework is proposed for the construction of mutual fund portfolios. The argumentation framework is employed in order to develop mutual funds performance models and to select a small set of mutual funds, which will compose the final portfolio. The knowledge engineering approach and tool development know-how, presented here-in,...
In the process of training support vector machines (SVMs) by decomposition methods, working set selection is an important technique, and some exciting schemes were employed into this field. To improve working set selection, we propose a new model for working set selection in sequential minimal optimization (SMO) decomposition methods. In this model, it selects B as working set without reselection...
In this paper we present a new approach for curve clustering designed for analysis of spatiotemporal data. Such kind of data contains both spatial and temporal patterns that we desire to capture. The proposed methodology is based on regression and Gaussian mixture modeling and the novelty of the herein work is the incorporation of spatial smoothness constraints in the form of a prior for the data...
Human-computer interaction requires efficient acquisition of the relevant information from the user. This poses high accuracy in the performance of the relevant systems, especially when visual information is used as the basic means to capture the user's information. At the same time, speed and efficiency under a variety of conditions (e.g, resolution, luminance) is required. From this perspective,...
Takagi-Sugeno Fuzzy Models within the framework of Orthonormal Basis Functions (OBF-TS Fuzzy Models) have shown to be an effective approach to nonlinear system identification and control due to several advantages they exhibit over those dynamic model topologies most commonly adopted in the literature. Despite all the theoretical advances and encouraging application results obtained so far, the automatic...
Statistical spam filters are known to be vulnerable to adversarial attacks. One such adversarial attack, known as the good word attack, thwarts spam filters by appending to spam messages sets of "good" words, which are common in legitimate e-mail but rare in spam. We present a counter attack strategy that first attempts to differentiate spam from legitimate e-mail in the input space, by...
Human behavior representation in military simulations is not sufficiently realistic, specially the decision making by synthetic military commanders. In order to address some of these deficiencies, we have developed a computer implementation of Recognition Primed Decision Making (RPD) model using Soar cognitive architecture and it is referred to as RPD-Soar agent in this paper. The proposed implementation...
This research project is headed for designing a rational believable agent with a goal based rational- emotional architecture which has to interact with humans in communicative scenarios by facial expressions. The proposed model defines interactions among rationality, personality and emotion to make rational decisions with emotional regulation and improve decision making process by means of applying...
Multiagent systems (MAS) are well suited to specify requirements far open physical complex systems. However, up to now, no method allows to actually build software/hardware hybrid MAS. This paper presents an original method far designing embedded MAS.
Online buyer coalition formation problem is an application of e-commerce and distributed agent technology. Most existing works in this topic involve social utility based approaches that assume the agents' utilities to be transferable. However, we argue that there are situations where the transferable utility model is not well suited for the problem, and that coalition stability is a more important...
Distributed constraint optimization is increasingly used for problem solving by multiple agents. However, there are situations where the system is made up of heterogeneous agents, for which the context, the structure, and the business rules define the interactions that are possible between them. As an example, supply chains are made up of interdependent business units having some form of customer-supplier...
Vehicular platoon are a promising approach to new transportation systems, with innovative capabilities, such as vehicle sharing and adaptability to demand. This paper presents a multiagent solution to the platoon control problem with a linear configuration. In our case, a platoon is a vehicle train composed of a head vehicle and a variable number of followers. The head vehicle is human-driven or autonomous,...
Unlike mono-agent systems, multi-agent planing addresses the problem of resolving conflicts between individual and group interests. In this paper, we are using a Decentralized Vector Valued Markov Decision Process (2V-DEC-MDP) in order to solve this problem. It uses an utility function which is returning a vector representing both individual and group interest. The individual interest of an agent,...
In this paper, we evaluated the efficacy of mined association rules between words for measuring the similarity between documents to enhance the text retrieval. In our experiments, for each document relevant to a query, we formed a group of documents having at least one common frequent set of words with the answer document. Then we measured the precision of the documents in the same group as an answer...
The presented study aims to provide for a generally higher level of safety for people in hazardous situations by using an agent-based intelligent adaptive system. A design of a software system for the prevention of earthquake secondary disasters is presented. The proposed system is to control consumer electronics and other potentially dangerous equipment in a household, and also to guide evacuation...
The present paper describes a Bayesian network approach to information retrieval (IR) from natural language texts in Greek. The network structure provides an intuitive representation of uncertainty relationships and the embedded conditional probability table is used by inference algorithms in an attempt to identify documents that are relevant to the user's needs, expressed in the form of Boolean queries...
Many real datasets have uncertain categorical attribute values that are only approximately measured or imputed. Uncertainty in categorical data is commonplace in many applications, including biological annotation, medial diagnosis and automatic error detection. In such domains, the exact value of an attribute is often unknown, but may be estimated from a number of reasonable alternatives. Current...
The k-nearest neighbour (kNN) method is simple but effective for classification. The bottleneck of kNN is it needs a good similarity measure which could be problematic in some cases especially for datasets containing categorical data. In this paper, a partial coverage based classificaiton (PCC) method is proposed which works without similarity measure and conversion for categorical data. Moreover,...
Spatial outliers are the spatial objects whose nonspatial attribute values are quite different from those of their spatial neighbors. Identification of spatial outliers is an important task for data mining researchers and geographers. A number of algorithms have been developed to detect spatial anomalies in meteorological images, transportation systems, and contagious disease data. In this paper,...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.