Agent-Based Software Engineering, Paradigm Shift, or Research Program Evolution

Information systems are deeply linked to human activities. Unfortunately, development methodologies have been traditionally inspired by programming concepts and not by organizational and human ones. This leads to ontological and semantic gaps between the systems and their environments. The adoption of agent orientation and multi-agent systems (MAS) helps to reduce these gaps by offering modeling tools based on organizational concepts (actors, agents, goals, objectives, responsibilities, social dependencies, etc.) as fundamentals to conceive systems through all the development process. Moreover, software development is becoming increasingly complex. Stakeholders' expectations are growing higher while the development agendas have to be as short as possible. Project managers, business analysts, and software developers need adequate processes and models to specify the organizational context, capture requirements, and build efficient and flexible systems.

Application of Computational Intelligence in Network Intrusion Detection

Intrusion detection system plays an important role in network security. However, network intrusion detection (NID) suffers from several problems, such as false positives, operational issues in high dimensional data, and the difficulty of detecting unknown threats. Most of the problems with intrusion detection are caused by improper implementation of the network intrusion detection system (NIDS). Over the past few years, computational intelligence (CI) has become an effective area in extending research capabilities. Thus, NIDS based upon CI is currently attracting considerable interest from the research community. The scope of this review will encompass the concept of NID and presents the core methods of CI, including support vector machine, hidden naïve Bayes, particle swarm optimization, genetic algorithm, and fuzzy logic. The findings of this review should provide useful insights into the application of different CI methods for NIDS over the literature, allowing to clearly define existing research challenges and progress, and to highlight promising new research directions.

A Tour of Lattice-Based Skyline Algorithms

A skyline query retrieves all objects in a dataset that are not dominated by other objects according to some given criteria. There exist many skyline algorithms which can be classified into generic, index-based, and lattice-based algorithms. This chapter takes a tour through lattice-based skyline algorithms. It summarizes the basic concepts and properties, presents high-performance parallel approaches, shows how one overcomes the low-cardinality restriction of lattice structures, and finally presents an application on data streams for real-time skyline computation. Experimental results on synthetic and real datasets show that lattice-based algorithms outperform state-of-the-art skyline techniques, and additionally have a linear runtime complexity.

Application of Fuzzy Sets and Shadowed Sets in Predicting Time Series Data

In recent years, several methods for forecasting fuzzy time series have been presented in different areas, such as stock price, student enrollments, climatology, production sector, etc. Choice of data partitioning technique is a central factor and it highly influences the forecast accuracy. In all existing works on fuzzy time series model, cluster with highest membership is used to form fuzzy logical relationships. But the position of the element within the cluster is not considered. The present study incorporates the idea of fuzzy discretization and shadowed set theory in defining intervals and uses the positional information of elements within a cluster in selection of rules for decision making. The objective of this work is to show the effect of the elements, lying outside the core area on forecast. Performance of the presented model is evaluated on standard datasets.

Design Patterns for Social Intelligent Agent Architectures Implementation

Multi-agent systems (MAS) architectures are popular for building open, distributed, and evolving software required by today's business IT applications such as e-business systems, web services, or enterprise knowledge bases. Since the fundamental concepts of MAS are social and intentional rather than object, functional, or implementation-oriented, the design of MAS architectures can be eased by using social patterns. They are detailed agent-oriented design idioms to describe MAS architectures as composed of autonomous agents that interact and coordinate to achieve their intentions like actors in human organizations. This chapter presents social patterns and focuses on a framework aimed to gain insight into these patterns. The framework can be integrated into agent-oriented software engineering methodologies used to build MAS. The authors consider the broker social pattern to illustrate the framework. The mapping from system architectural design (through organizational architectural styles), to system detailed design (through social patterns), is overviewed with a data integration case study.

Modeling Fish Population Dynamics for Sustainability and Resilience

Conservation of any living creature is very vital to maintain the balance of ecosystem. Fish is one of the most regularly consumed living creatures, and hence its conservation is essential for sustainable fish population to help maintain a balanced ecosystem. It is possible to keep a sustainable fish population only if a balance between consumption and growth of fish population can be ensured. Developing a model on fish population dynamics is needed to achieve this objective. In this chapter, the authors present a system dynamics model. This model will provide the scientific tools for determining fish population, its growth, and harvesting. The model's sensitivity to changes in key parameters and initial values resulting from the changes in basic scenarios and boundary conditions was tested several times. Model results show that fish birth, growth, stocks, and catch can be controlled timely and effectively in different real-world changing conditions to maintain a sustainable fish population.

What Is It Like to Be a Cyborg?

In this chapter, the author describes his personal experience in experimenting as a cyborg (part biology/part technology) by having technology implanted in his body, which he lived with over a period. A look is also taken at the author's experiments into creating cyborgs by growing biological brains which are subsequently given a robot body. The experiments are dealt with in separate sections. In each case the nature of the experiment is briefly described along with the results obtained and this is followed by an indication of the experience, including personal feelings and emotions felt in and around the time of the experiments and subsequently as a result of the experiments. Although the subject can be treated scientifically from an external perspective, it is really through individual, personal experience that a true reflection can be gained on what might be possible in the future.

Search for an Optimal Solution to Vague Traffic Problems Using the PSK Method

There are several algorithms, in literature, for obtaining the fuzzy optimal solution of fuzzy transportation problems (FTPs). To the best of the author's knowledge, in the history of mathematics, no one has been able to solve transportation problem (TP) under four different uncertain environment using single method in the past years. So, in this chapter, the author tried to categories the TP under four different environments and formulates the problem and utilizes the crisp numbers, triangular fuzzy numbers (TFNs), and trapezoidal fuzzy numbers (TrFNs) to solve the TP. A new method, namely, PSK (P. Senthil Kumar) method for finding a fuzzy optimal solution to fuzzy transportation problem (FTP) is proposed. Practical usefulness of the PSK method over other existing methods is demonstrated with four different numerical examples. To illustrate the PSK method different types of FTP is solved by using the PSK method and the obtained results are discussed.

Artificial-Intelligence-Based Service-Oriented Architectures (SOAs) for Crisis Management

The complexity of crisis-related situations requires the use of advanced technological infrastructures. In order to develop such infrastructures, specific architectures need to be applied such as the service-oriented architectures (SOAs). The purpose of this chapter is to indicate how SOAs can be used in modern crisis management systems, such as the ATHENA system. The chapter underlines the need for a detailed study of specific biological systems, such as the human brain's hippocampus which follows the current, intense attempts of improvement of the current artificial-intelligence-based systems and the development of a new area in artificial intelligence. A number of conclusions are drawn on how biologically inspired systems can benefit the development of service-oriented architectures.

An Electric Wheelchair Controlled by Head Movements and Facial Expressions

A bio-signal-based human machine interface is proposed for hands-free control of a wheelchair. An Emotiv EPOC sensor is used to detect facial expressions and head movements of users. Nine facial expressions and up-down head movements can be chosen to form five commands: move-forward and backward, turn-left and right, and stop. Four uni-modal modes, three bi-modal modes, and three fuzzy bi-modal modes are created to control a wheelchair. Fuzzy modes use the users' strength in making the head movement and facial expression to adjust the wheelchair speed via a fuzzy logic system. Two subjects tested the ten modes with several command configurations. Means, minimum, and maximum values of the traveling times achieved by each subject in each mode were collected. Results showed that both subjects achieved the lowest mean, minimum and maximum traveling times using fuzzy modes. Statistical tests showed that there were significant differences between traveling times of fuzzy modes of subject B and traveling times of bi-modal modes and those of the respective fuzzy modes of both subjects.