Artificial Intelligent

Word sense disambiguation (WSD) is the problem of determining the sense of a multi-sense word in a given context. It is one of the important processes needed for natural language processing applications. Inductive Logic Programming (ILP) is the area of artificial intelligence which contains machine learning and logic programming. It aims to build first- order theories from examples and background knowledge, which are also represented by first- order clauses. The richness of first order logic employed in ILP can hopefully provide advantages for NLP applications such as WSD. In this study, a corpus-based WSD application is improved by using ILP.

Abstract: - How can the performance of a social robot be measured? Are existing metrics and techniques appropriate for physically and socially embodied autonomous mobile robots? With the rapid expansion of robust robotic systems from strong industrial applications to ...

Abstract: The work reported here is the result of a study done within a larger project on the``Semantics of Natural Languages''viewed from the field of Artificial Intelligence and Computational Linguistics. In this project, we have chosen a corpus of insurance claim reports. These texts deal with a relatively circumscribed domain, that of road traffic, thereby limiting the extra-linguistic knowledge necessary to understand them. Moreover, these texts present a number of very specific characteristics, insofar as they are written in a quasi- ...

To gain more insight into the process of teaching and learning mathematics, we experimented during the Fall of 2003 and the spring of 2004 with some calculus chat bots. These bots know an encyclope- dic glossary of mathematics definitions as well as general knowledge background and can solve simple mathematical template problems posed in colloquial language. The bot "Sofia" can also interact with computer algebra systems like Pari or Mathematica to solve simple pre-wired calculus problems.

Artificial intelligence techniques useful in diagnosis can be classified into eight categories. Among these techniques the integrated diagnostic techniques are often presented as the most efficient to resolve practical problems. This approach may lack however some flexibility to be applied in many application domains, when the role played by users takes an important part of the diagnosis process. Hypertext systems

... for that taking selected ordering parameters as input is much efficient for modeling. ... Taleb-Bendiab, “Performance Evaluation for Self-Healing Distributed Services and Fault Detection Mechanisms,” Journal ... 4].M. Steinder and AS Sethi, “A Survey of Fault Localization Techniques ...

The paper presents a short survey of three topics: modern sensor networks, distributed parameter systems and estimation techniques, especially using artificial intelligence tools, to be involved in the new domain of identification of distributed parameter systems, based on sensor networks and artificial intelligence. As smart and small devices the modern sensors are capable to be implemented in large distributed parameter systems. Sensor networks, with hundred and thousands of ad-hoc tiny sensor nodes spread across a geographical, are acting as a distributed sensor in a distributed parameter system. Sensor network topics, sensor network architectures and sensor network applications are presented. Examples of distributed parameter systems with large application in practice as the process of heat conduction, applications related to electricity domain, motion of fluids, the processes of cooling and drying, phenomenon of diffusion and other applications are presented. The identification...

Answer Set Programming is a very convenient framework to represent various problems issued from Artificial Intelligence (nonmonotonic reasoning, planning, diagnosis...). Furthermore, it can be used to neatly encode combinatorial problems. In all cases, the solutions are obtained as sets of literals: the Answer Sets. Ant Colony Optimization is a general metaheuristics that has been already successfully used to solve hard combinatorial problems (traveling salesman problem, graph coloring, quadratic assignment...). It is based on the collective behavior of artificial ants exploring a graph and exchanging pieces of information by means of pheromone traces. The purpose of this work is to show how Ant Colony Optimization can be used to compute an answer set of a logic program.

This paper presents an extension of MOVICAB-IDS, a Hybrid Intelligent Intrusion Detection System characterized by incorporating temporal control to enable real-time processing and response. The original formulation of MOVICAB-IDS combines artificial neural networks and case-based reasoning within a multiagent system to perform Intrusion Detection in dynamic computer networks. The contribution of the anytime algorithm, one of the most promising to adapt Artificial Intelligent techniques to real-time requirements; is comprehensively presented in this work.

This paper proposes an intrusion detection and prediction system based on uncertain and imprecise inference networks and its implementation. Giving a historic of sessions, it is about proposing a method of supervised learning doubled of a classifier permitting to extract the necessary knowledge in order to identify the presence or not of an intrusion in a session and in the positive case to recognize its type and to predict the possible intrusions that will follow it. The proposed system takes into account the uncertainty and imprecision that can affect the statistical data of the historic. The systematic utilization of an unique probability distribution to represent this type of knowledge supposes a too rich subjective information and risk to be in part arbitrary. One of the first objectives of this work was therefore to permit the consistency between the manner of which we represent information and information which we really dispose.

Abstract. Motivation plays a key role in the learning process. This paper describes an experience in the context of undergraduate teaching of Artificial Intelligence at the Computer Science Department of the Faculty of Sciences in the University of Porto. A sophisticated competition framework, which involved Prolog programmed contenders and game servers, including an appealing GUI, was developed to motivate students on the deepening of the topics covered in class. We report on the impact that such a competitive setup caused on ...