THE CSI JOURNAL ON COMPUTER SCIENCE AND ENGINEERING
Year:2005 | Volume:3 | Issue:2-4 (B)|Papers Count:5

This paper presents a new architecture for implementing intelligent agents cooperating in a special Multi Agent environment, namely the RoboCup Rescue Simulation System. This is a three layered architecture which customized for cooperating three kinds of agents to minimize damages, caused by a big earthquake in rescue simulation environment. Structural decision making algorithms are combined with heuristic ones in this model. One of advantage of this architecture is supporting both Centralized and Distributed multi agent systems. At the end comparing this new architecture with those which be used till now could show the strength of new architecture.

Flexible automated negotiation, specially in dynamic, uncertain and unpredictable environments can increase likelihood and quality of agreements and promote agent's properties. For developing flexible negotiation systems, first we should define and formalize flexibility in negotiation. A precise and clear formulation of flexibility in agent-based negotiations has not reported explicitly in the literature. In this paper, we describe the benefits of flexible negotiation and we provide a set of requirements for flexible negotiation in agent-based systems. The main contribution of this paper is an explicit formulation of flexibility in negotiation systems. Based on this formulation a survey and analysis of the existing works in the automated negotiation literature is presented and results are given. Then, according to the proposed formulation, we will show that negotiation systems that are designed and implemented based on argumentation-based approach are flexible and can operate in more dynamic and unpredictable environments.

Fingerprint is one of the most imp0l1ant indexes that can be applied to human verification and identification. In the recent decade, with the population explosion and tremendous increase in fingerprint databases, automation of identification has been unavoidable. Fingerprint classification decreases the time of search for an unknown image in large databases. In this research, translation and rotation invariant features are extracted from spectrum of the fingerprint image, and a new tessellation on the frequency spectrum based on an appropriate definition of frequency concept in the fingerprint application, has been designed. The extracted features obtain not only information from frequency of ridges but also valuable information from direction of ridges in the fingerprint images. Features are classified with Probabilistic Neural Network. FVC2000 and FVC2002 databases are used to assess the proposed algorithm. The proposed algorithm provides an accuracy and speed of classification more than previously reported in the literature. We have obtained an accuracy of 93.4 percent with a rejection ratio 2.8 percent for the seven-class task and for the six-class classification task an accuracy of 95.1 percent with a rejection ratio 2.4 percent is achieved.

As the number of elements in large-scale massively parallel computers, Multiprocessors System-on-Chip (MP-SoCs), and peer-to-peer communication networks increases, the probability of component failure becomes significant. Consequently, fault-tolerance turns out to be a key issue in the design of such systems. Adaptive routing algorithms have been frequently suggested as a means of improving communication performance in such systems these algorithms, unlike deterministic routing, can utilize network state information to exploit the presence of multiple paths. Before such schemes can be successfully incorporated in networks, it is necessary to have a clear understanding of the factors which affect their performance potential this paper investigates the performance of nine prominent adaptive fault-tolerant routing algorithms in wormhole-switched 2-D tori with a routing scheme suggested by Chalasani and Boppana, as an instance of a fault-tolerant method. The suggested scheme is widely used in the literature to achieve high adaptivity and support interprocessor communications in massively parallel computers due to its ability to preserve both communication performance and fault-tolerant demands in these networks. The performance measures studied in the paper are the throughput, average message latency and average usage of virtual channels per node. Results obtained through simulation suggest two classes of presented routing schemes as high performance candidates in most faulty networks Furthermore; we propose an analytical model to assess the performance behavior of a fully adaptive routing which has been shown to be one of the most efficient routings in the torus networks. The validity of the model is demonstrated by comparing analytical results with those obtained through simulation experiments.

Microphone array processing techniques have generated a tremendous interest in both theoretical and applied areas, especially, over the past decade. So long as an array performs a type of spatial filtering, the dimension of array will determine the acceptable frequency-range of the incoming waves. Consequently, it IS well known that, miniature microphone arrays are not appropriate for audio applications. In this paper, we introduce a novel technique to utilize miniature microphone arrays for detecting audio signals. Besides the problem of low sensitivity of such arrays in low frequency beamforming, due to dealing with wideband audio signals, is resolved. We start our discussion with a Delay and-Sum beam former, and extend it to the GSC-based beam former, as an example of popular beamformers. Constant directivity is an important result of the proposed approach