scholarly journals EMPLOYING AGENTS IN DESCRIPTIVE MINING

2016 ◽  
Vol 4 (2) ◽  
pp. 111-120
Author(s):  
R. Sabitha ◽  
Karthik
Keyword(s):  
Data Mining ◽  
Intelligent Agents ◽  
Intelligent Systems ◽  
Agent Technology ◽  
Distributed Environment ◽  
New Techniques ◽  
Distributed Problem Solving ◽  
Agent Mining ◽  
Intelligent Information ◽  
Different Sources

Agent technology and Data Mining have emerged as two of the prominent areas in information sciences. An effort has been activated towards the interaction and integration between agent technology and data mining which is referred to as “AGENT MINING”. Data Mining is the process of extracting interesting information or patterns from large volumes of data. Agents comprise a powerful technology for the analysis, design and implementation of autonomous intelligent systems that can handle distributed problem-solving, cooperation, coordination, communication, and organization in a multiplayer environment. This agent uses information technology to find trends and patterns in an abundance of information from many different sources. The user can sort through this information in order to find whatever information they are seeking. Intelligent agents are today accepted as powerful tools for data mining in a distributed environment. The interaction and integration between agent and mining has potential to not only strengthen either side, but generate new techniques for developing more powerful intelligence and intelligent information processing systems. This paper discusses how agents are used in the various descriptive models of Data Mining. The various challenges and methodologies are analyzed and it clearly indicates the need for and the promising potential of agent mining for the mutual enhancement of both fields and for the creation of super-intelligent systems. Even though many researchers have been committed, more efforts are required to develop techniques and systems in practical perspectives.

The Central Role of Cognitive Computations in Human-Information Interaction

2018 ◽  
Author(s):  
Wai-Tat Fu ◽  
Jessie Chin ◽  
Q. Vera Liao
Keyword(s):  
Information Systems ◽  
Cognitive Science ◽  
Intelligent Systems ◽  
Intelligent System ◽  
Levels Of Abstraction ◽  
Intelligent Information Systems ◽  
Emergent Behaviour ◽  
Information Interaction ◽  
Intelligent Information

Cognitive science is a science of intelligent systems. This chapter proposes that cognitive science can provide useful perspectives for research on technology-mediated human-information interaction (HII) when HII is cast as emergent behaviour of a coupled intelligent system. It starts with a review of a few foundational concepts related to cognitive computations and how they can be applied to understand the nature of HII. It discusses several important properties of a coupled cognitive system and their implication to designs of information systems. Finally, it covers how levels of abstraction have been useful for cognitive science, and how these levels can inform design of intelligent information systems that are more compatible with human cognitive computations.

scholarly journals Data Mining and Intelligent Agents for Supporting Mass Customization in the Automotive Industry

10.5772/13135 ◽  
2011 ◽  
Author(s):  
Efthimia Mavridou ◽  
Dimitrios Tzovaras ◽  
Evangelos Beakiaris ◽  
Pavlos Spanidis ◽  
Maria Gemou ◽  
...  
Keyword(s):  
Data Mining ◽  
Automotive Industry ◽  
Mass Customization ◽  
Intelligent Agents

Data mining in distributed environment: a survey

2017 ◽  
Vol 7 (6) ◽  
Author(s):  
Wensheng Gan ◽  
Jerry Chun‐Wei Lin ◽  
Han‐Chieh Chao ◽  
Justin Zhan
Keyword(s):  
Data Mining ◽  
Distributed Environment

scholarly journals Agents’ ontologies negotiation in cohesive hybrid intelligent multi-agent systems

2021 ◽  
Vol 2094 (3) ◽  
pp. 032033
Author(s):  
I A Kirikov ◽  
S V Listopad ◽  
A S Luchko
Keyword(s):  
Intelligent Agents ◽  
Intelligent Systems ◽  
Multi Agent Systems ◽  
Labor Costs ◽  
Joint Work ◽  
Working Process ◽  
Agent Systems ◽  
Development Teams ◽  
Multi Agent ◽  
Domain Models

Abstract The paper proposes the model for negotiating intelligent agents’ ontologies in cohesive hybrid intelligent multi-agent systems. Intelligent agent in this study will be called relatively autonomous software entity with developed domain models and goal-setting mechanisms. When such agents have to work together within single hybrid intelligent multi-agent systems to solve some problem, the working process “go wild”, if there are significant differences between the agents’ “points of view” on the domain, goals and rules of joint work. In this regard, in order to reduce labor costs for integrating intelligent agents into a single system, the concept of cohesive hybrid intelligent multi-agent systems was proposed that implement mechanisms for negotiating goals, domain models and building a protocol for solving the problems posed. The presence of these mechanisms is especially important when building intelligent systems from intelligent agents created by various independent development teams.

scholarly journals Failure Analysis in University and Computer Science Contexts With Data Mining

2020 ◽  
Author(s):  
Daniela De Souza Gomes ◽  
Marcos Henrique Fonseca Ribeiro ◽  
Giovanni Ventorim Comarela ◽  
Gabriel Philippe Pereira
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Failure Analysis ◽  
Computer Science ◽  
Educational Administration ◽  
Intelligent Systems ◽  
Data Set ◽  
Data Mining Techniques ◽  
Study Case ◽  
Support Students

High failure rates are a worrying and relevant problem in Brazilian universities. From a data set of student transcripts, we performed a study case for both general and Computer Science contexts, in which Data Mining Techniques were used to find patterns concerning failures. The knowledge acquired can be used for better educational administration and also build intelligent systems to support students’ decision making.

scholarly journals Software Platform for Designing and Running Artificial Intelligence Competitions with a Visualization Subsystem

2019 ◽  
Author(s):  
Дмитрий Александрович Коростелев ◽  
Dmitriy Aleksandrovich Korostelev ◽  
Алексей Радченко ◽  
Aleksey Radchenko ◽  
Никита Сильченко ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Agents ◽  
Intelligent Systems ◽  
Software Platform ◽  
Main Approach ◽  
Specialized Software ◽  
Operational Testing ◽  
New Ideas ◽  
Systems Simulation

The paper describes the solution to the problem of testing the efficiency of new ideas and algorithms for intelligent systems. Simulation of interaction of the corresponding intelligent agents in a competitive form implementing different algorithms is proposed to use as the main approach to the solution. To support this simulation, a specialized software platform is used. The paper describes the platform developed for running competitions in artificial intelligence and its subsystems: a server, a client and visualization. Operational testing of the developed system is also described which helps to evaluate the efficiency of various algorithms of artificial intelligence in relation to the simulation like "Naval Battle".

Intelligent information systems and artificial intelligence methods

2021 ◽  
Author(s):  
Aleksandr Andreychikov ◽  
Ol'ga Andreychikova
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
Information Science ◽  
Federal State ◽  
Construction Technology ◽  
Intelligent Information Systems ◽  
Engineering And Technology ◽  
Subject Areas ◽  
Intelligent Information ◽  
State Educational

The textbook discusses the methods of artificial intelligence and their application to solve problems from various subject areas. Methods of acquisition, representation and processing of knowledge in intelligent systems, as well as technologies for designing and implementing intelligent systems, are described. Special attention is paid to the application of intelligent systems for the selection of collective solutions, the design of complex systems( objects), the analysis and forecasting of the enterprise. Meets the requirements of the federal state educational standards of higher education of the latest generation. For students enrolled in groups of training master's degree program "Management in technical systems", "Computer and information science", "computer science", "engineering and technology land transport", "engineering and construction technology", "Photonics, instrumentation, optical and biotechnical systems and technology", "aerospace engineering", "engineering and technologies of shipbuilding and water transport", and also in the areas of "automation of technological processes and productions", "mechatronics and robotics".

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