Accurate and swift responses are crucial to Intrusion Detection Systems (IDSs), especially if automatic abortion mechanisms are running. In keeping with this idea, this work presents an extension of a Hybrid Intelligent IDS characterized by incorporating temporal control to facilitate real-time processing. The hybrid intelligent -IDS has been conceived as a Hybrid Artificial Intelligent System ...

Recently, computational agents received significant attention in computer science research community. In fact, intelligent agents methodology is a powerful artificial intelligence technology showing considerable promise as a new paradigm for mainstream software development and able to offer new ways of abstraction, decomposition, and organization that fit well with our natural view of the world...

Provision of data to intelligent systems, for decision making, by making use of World Wide Web is one of the most promising areas of research in Artificial Intelligence. When a task is given to an intelligent system, its solution is unknown. It is the job of Artificial Intelligent (AI) systems to find the best solution based on the information available to it. With development in web technology...

This article describes an intelligent system architecture that based on neural networks, expert systems and negotiating agents technologies is designed to optimize intelligent building’s performance. By understanding a building as a dynamic entity capable of adapting itself not only to changing environmental conditions but also to occupant’s living habits, high standards of comfort and user sat...

In this paper we present a methodology to specify Multiagent Systems, called MASINA. MASINA is based on MAS-CommonKADS; we use the models presented in this methodology to propose some extensions, modifications and substitutions allowing to describe the intelligent characteristics of an agent or group of agents, to use intelligent techniques for the accomplishment of tasks (e.g. artificial neura...

Deep machine learning and reinforcement learning are two complementing fields within the study of intelligent systems. When combined, it is argued that they offer a promising path for achieving artificial general intelligence (AGI). This chapter outlines the concepts facilitating such merger of technologies and motivates a framework for building scalable intelligent machines. The prospect of ut...