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Abstract: This paper presents a planning model integrated within a TB-CBP-BDI real-time intelligent agent that provides special abilities for planning in a predictable time, which makes its use especially appropriate in systems where certain temporal constraints must be satisfied. The proposed TB-CBP-BDI real-time agent is the core of a multi-agent system that manages security issues in industrial environments, where time constraints are a key factor. The proposed planning model facilitates the automatic temporal bounded reorganization of tasks to provide the system with adaptation abilities to the changes that occur in the environment. The planning mechanism focuses on optimizing industrial and manufacturing processes, specifically the tasks performed by the available security entities in these environments. Additionally, several Ambient Intelligence technologies such as QR-CODES, GPS, Wi-Fi and HSDPA are used to develop the intelligent environment that was tested and analyzed in this study. [Copyright &y& Elsevier]

Abstract: The use of architectures based on services and multi-agent systems has become an increasingly important part of the solution set used for the development of distributed systems. Nevertheless, these models pose a variety of problems with regards to security. This article presents the Adaptive Intrusion Detection Multi-agent System (AIDeMaS), a mechanism that has been designed to detect and block malicious SOAP messages within distributed systems built by service based architectures. AIDeMaS has been implemented as part of FUSION@, a multi-agent architecture that facilitates the integration of distributed services and applications to optimize the construction of highly-dynamic multi-agent systems. One of the main features of AIDeMaS is that is employs case-based reasoning mechanisms, which provide it with great learning and adaptation capabilities that can be used for classifying SOAP messages. This research presents a case study that uses the ALZ-MAS system, a multi-agent system built around FUSION@, in order to confirm the effectiveness of AIDeMaS. The preliminary results are presented in this paper. [Copyright &y& Elsevier]

Abstract: Microarray technology provides a great amount of data requiring analysis, and the use of new intelligent algorithms that identify the relevant information for the classification process has become essential. This study presents a classification tool called MicroCBR that uses the case-based reasoning paradigm and incorporates a novel filtering technique based on statistical methods, a new clustering technique that uses ESOINN (Enhanced Self-Organizing Incremental Neuronal Network), and a knowledge extraction technique based on the J48 algorithm. MicroCBR has been applied to classify 91 CLL patients and the results obtained are shown in this paper. [Copyright &y& Elsevier]

Abstract: Security is a major concern when service environments are implemented. This has led to the proposal of a variety of specifications and proposals based on soft computing methods to provide the necessary security for these environments. However, most proposed approaches focus only on ensuring confidentiality and integrity, without putting forward mechanisms that ensure the availability of services and resources offered. A considerable number of attack mechanisms can lead to a web service system crash. As a result, the web service cannot allow access to authorized users. This type of attack is a so-called denial of service attack (DoS) which affects the availability of the services and recourses available. This article presents a novel soft computing-based approach to cope with DoS attacks, but unlike existing solutions, our proposal takes into account the different soft computing mechanisms that can lead to a DoS attack. Our approach is based on a real time classifier agent that incorporates a mixture of experts to choose a specific classification technique depending on the feature of the attack and the time available to solve the classification. With this scheme it is possible to divide the problem into subproblems, solving the classification of the web service requests in a more simple and effective way and always within a time bound interval. This research presents a case study to evaluate the effectiveness of the approach and also presents the preliminary results obtained with an initial prototype. [Copyright &y& Elsevier]

The exchange of CO_{2} between the atmosphere and the ocean surface is a problem that has become increasingly important due to its impact on climatic behavior. Given the large quantity of sources of information available for studying the CO_{2} problem, it is necessary to provide innovative solutions that facilitate the automation of certain tasks and incorporate decision support systems to obtain a better understanding of this phenomenon. This paper presents a multiagent architecture aimed at providing solutions for monitoring the interaction between the atmosphere and the ocean. The ocean surface and the atmosphere exchange carbon dioxide. This process is can be modeled by a multiagent system with advanced learning and adaption capabilities. The proposed multiagent architecture incorporates CBR-agents that integrate novel strategies that both monitor the parameters that affect the interaction, and facilitate the creation of models. The system was tested and this paper presents the results obtained. [ABSTRACT FROM AUTHOR]

Microarray technology can measure the expression levels of thousands of genes in an experiment. This fact makes the use of computational methods in cancer research absolutely essential. One of the possible applications is in the use of Artificial Intelligence techniques. Several of these techniques have been used to analyze expression arrays, but there is a growing need for new and effective solutions. This paper presents a Case-based reasoning (CBR) system for automatic classification of leukemia patients from microarray data. The system incorporates novel algorithms for data mining that allow filtering, classification, and knowledge extraction. The system has been tested and the results obtained are presented in this paper. [ABSTRACT FROM AUTHOR]

This paper presents an intelligent environment developed for monitoring patients’ health care in execution time in hospital environments. The CBPMP (case-based planner for monitoring patients) is an autonomous deliberative case-based planner designed to plan the nurses’ working time dynamically, to maintain the standard working reports about the nurses’ activities, and to guarantee that the patients assigned to the nurses are given the right care. The planner operates in wireless devices and is integrated with complementary software into an intelligent environment, named AmI-P (Ambient Intelligence for patients). CBPMP description, its relationship with the complementary technology, and preliminary results of system prototype in a real environment are presented. [Copyright &y& Elsevier]

Abstract: This paper introduces the SHOMAS Multiagent System that provides guidance on leisure facilities and suggestions for shopping in malls. The multiagent architecture incorporates reactive and deliberative agents that take decisions automatically. The developed deliberative agent provides suggestions in execution time, with the help of case-based planners. This agent is described together with its guidance and suggestion mechanism. SHOMAS has been tested successfully, and the results obtained are presented in this paper. [Copyright &y& Elsevier]

Abstract: During the last years the use of Web Service-based applications has notably increased. However, the security has not evolved proportionally, which makes these applications vulnerable and objective of attacks. One of the most common attacks requiring novel solutions is the denial of service attack (DoS), caused for the modifications introduced in the XML of the SOAP messages. The specifications of existing security standards do not focus on this type of attack. This article presents the S-MAS architecture as a novel adaptive approach for dealing with DoS attacks in Web Service environments, which represents an alternative to the existing centralized solutions. S-MAS proposes a distributed hierarchical multi-agent architecture that implements a classification mechanism in two phases. The main benefits of the approach are the distributed capabilities of the multi-agent systems and the self-adaption ability to the changes that occur in the patterns of attack. A prototype of the architecture was developed and the results obtained are presented in this study. [ABSTRACT FROM AUTHOR]