Systems And Network Management

Published Date: 02 Nov 2017

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In artificial intelligence, an intelligent agent (IA) is an autonomous entity which observes through sensors and acts upon an environment using actuators (i.e. it is an agent) and directs its activity towards achieving goals (i.e. it is rational). Intelligent agents may also learn or use knowledge to achieve their goals. They may be very simple or very complex: a reflex machine such as a thermostat is an intelligent agent, as is a human being, as is a community of human beings working together towards a goal. Intelligent agents are often described schematically as an abstract functional system similar to a computer program. For this reason, intelligent agents are sometimes called abstract intelligent agents (AIA) to distinguish them from their real world implementations as computer systems, biological systems, or organizations. Some definitions of intelligent agents emphasize their autonomy, and so prefer the term autonomous intelligent agents. Still others considered goal-directed behavior as the essence of intelligence and so prefer a term borrowed from economics, "rational agent".

Intelligent agents in artificial intelligence are closely related to agents in economics, and versions of the intelligent agent paradigm are studied in cognitive science, ethics, the philosophy of practical reason, as well as in many interdisciplinary socio-cognitive modeling and computer social simulations.

Intelligent agents are also closely related to software agents (an autonomous computer program that carries out tasks on behalf of users). In computer science, the term intelligent agent may be used to refer to a software agent that has some intelligence, regardless if it is not a rational agent by Russell and Norvig's definition. For example, autonomous programs used for operator assistance or data mining (sometimes referred to as bots) are also called "intelligent agents".

CHARACTERISTICS OF INTELLIGENT AGENTS

While no definitive definition of what makes a computer program an intelligent agent currently exists, researchers have reached some consensus on the common attributes of intelligent agents:

Autonomy - an intelligent agent must be capable of working without human supervision.

Self-learning - an intelligent agent should be capable of changing their behaviour according totheir accumulated knowledge.

Proactive - an intelligent agent should be capable of making decisions based on its own initiative.

Communication - an intelligent agent needs to be able to communicate with other systems and agents, while also communicating with the end user in natural language.

Co-operation - some of the more advanced intelligent agents should be able to act in unison with other agents to carry out complex tasks.

Mobility - an intelligent agent will need to be mobile, to enable it to travel throughout computer systems in order to accumulate knowledge and carry out tasks.

Goal Driven - all intelligent agents must have a goal, a user-defined purpose, and then act in accordance with that purpose. Not all agents must possess every one of these attributes to be considered valid. For example, each agent is likely to have different knowledge, capabilities, reliability, resources and responsibilities that will all have a bearing on the design of the agent

APPLICATION OF INTELLIGENT AGENT

Here are some of the examples that use intelligent agent which illustrate some of the important ways intelligent agents can help solve real problems and make today's computer system easier to use. 

Customer Help Desk 

Customer help desk job is to answer calls from customers and find the answer to their problems. When customers call with a problems, the help desk person manually look up answers from hardcopy manuals, but those hardcopy manuals have been replaced with searchable CD-ROM collections, and some companies even offer searches over the Internet. Instead of hiring help desk consultants, or having the customers search through the internet for an answer, with intelligent agent, customer describe the problem and the agent automatically searches the appropriate databases (either CD-ROM, or the Internet), then presents a consolidated answer with the most likely first. This is a good example of using intelligent agent to find and filter information. 

Web Browser Intelligent 

A web browser intelligent, such as an IBM Web Browser Intelligent is an agent which helps you keep track of what web site you visited and customizes your view of the web by automatically keeping a bookmark list, ordered by how often and how recent you vis it the site. It allows you to search for any words you've seen in your bookmark track, and takes you back to the site allowing you to find and filter quickly. It also help you find where you were by showing you all the different track you took starting at the current page. It also let you know by notifying you when sites you like are updated, and it could also automatically download pages for you to browse offline. 

Personal Shopping Assistant 

IBM's Personal Shopping Assistant uses intelligent agent technology to help the Internet shopper or the Internet shop owner to find the desired item quickly without having to browse page after page of the wrong merchandise. With the Personal Shopping Assistant, stores and merchandise are customized as the intelligent agent learned the shopper's preferences as he/she enters in any on-line mall or stores or looking at specific merchandise. It could also arrange the merchandise so that the items you like t he most are the first one you see. Finally, Personal Shopping Assistant automates your shopping experience by reminding you to shop when a birthday, an anniversaries, or item that is on sale occurred. 

Systems and Network Management

Systems and network management is one of the earliest application areas to be enhanced using intelligent agent technology. The movement to client/server computing has intensified the complexity of systems being managed, especially in the area of LANs, and as network centric computing becomes more prevalent, this complexity further escalates. Users in this area(primarily operators and system administrators) need greatly simplified management, in the face of rising complexity. Agent architectures have existed in the systems and network management area for some time, but these agents are generally "fixed function" rather than intelligent agents. However, intelligent agents can be used to enhance systems management software. For example, they can help filter and take automatic actions at a higher level of abstraction, and can even be used to detect and react to patterns in system behaviour. Further, they can be used to manage large configurations dynamically.

 

Electronic Commerce

Currently, commerce is almost entirely driven by human interactions; humans decide when to buy goods, how much they are willing to pay, and so on. But in principle, there is no reason why some commerce cannot be automated. By this, we mean that some commercial decision making can be placed in the hands of agents.

Intelligent agent technology is the next logical step in overcoming some shortcomings in e-commerce. Namely, successful computer systems underlying ecommerce require judgment and the knowledge of experts such as buyers, contract negotiators and marketing specialists . It is useful to explore the roles of agents as mediators in electronic commerce in the context of a common framework.

Identification: This stage characterizes the buyer becoming aware of some unmet need by

stimulating through product information. Agents can play an important role for those purchases that are repetitive (supplies) or predictable habits). One of the oldest and simplest examples of software agents are so called "monitors": continuously running programs which monitor a set of sensors or data streams and take action when a certain pre-specified condition apply . There are many examples in abundant use, one very familiar is a "notification agent" called "Eyes" by Amazon.com, which monitors the catalog of books for sale and notifies the customer when certain events occur that may be of interest to the customer (e.g., when a new book in category X becomes available).

Brokering: once a buyer has identified a need to make a purchase (possibly with the

assistance of a monitor agent), the buyer has to determine what to buy through a critical evaluation of retrieved product information. There are several agents systems that lower consumers’ search cost when deciding which products best meet their needs: PersonaLogic, Firefly, and Tete-a-Tete .The result of this stage is a consideration set of goods.

Negotiation: in this stage, price and other terms of the transaction are settled on. Real-world

negotiation increases transaction costs that may be too high for either consumers or merchants. There are also impediments in the real world to using negotiation such as time constraints, frustrations, all parties to be geographically co-located etc., which mostly disappear in the digital world. The majority of business-to-business transactions involve negotiation. In retail, we are mostly familiar with fixed prices. The benefit of dynamically negotiating the price for a product instead of fixing it is that it relieves the merchant from needing to determine the value of the good a priori .Rather, this burden is pushed to the marketplace.

Business Process Management

Company managers make informed decisions based on a combination of judgment and information from many departments. Ideally, all relevant information should be brought together before judgment is exercised. However obtaining pertinent, consistent and up-to-date information across a large company is a complex and time consuming process. For this reason, organizations have sought to develop a number of IT systems to assist with various aspects of the management of their business processes.

Industrial Applications

Industrial applications of agent technology were among the first to be developed: as early as 1987,Parunak reports experience with applying the contract net task allocation protocol in a manufacturing environment(see below). Today, agents are being applied in a wide range of industrial applications

process control

manufacturing

air traffic control

Medical Applications

Medical informatics is a major growth area in computer science: new applications are being found for computers every day in the health industry. It is not surprising, therefore, that agents should be applied in this domain. Two of the earliest applications are in the areas of health care and patient monitoring.

Entertainment

The leisure industry is often not taken seriously by the computer science community. Leisure applications are frequently seen as somehow peripheral to the ‘serious’ applications of computers. And yet leisure application such as computer games can be extremely lucrative –consider the number of copies of ‘Quake’ sold since its release in 1996. Agents have an obvious role in computer games, interactive theater, and related virtual reality applications: such systems tend to be full of semi-autonomous animated characters, which can naturally be implemented as agents.

Games

Interactive Theater and Cinema

Mail and Messaging:

Messaging software (such a software for e-mail) has existed for some time, and is also an area where intelligent agent function is currently being used. Users today want the ability to automatically prioritise and organise their e-mail, and in the future, they would like to do even more automatically, such as addressing mail by organisational function rather than by person. Intelligent agents can facilitate all these functions by allowing mail handling rules to be specified ahead of time, and letting intelligent agents operate on behalf of the user according to those rules.Usually it is also possible (or at least it will be) to have agents deduce these rules by observing a user's behaviour and trying to find patterns in it.

Collaboration

Collaboration is a fast-growing area in which users work together on shared documents, using personal video-conferencing, or sharing additional resources through the network. One common denominator is shared resources; another is teamwork. Both of these are driven and

supported by the move to network centric computing. Not only do users in this area need an infrastructure that will allow robust, scaleable sharing of data and computing resources, they also need other functions to help them actually build and manage collaborative teams of people, and manage their work products. One of the most popular and most heard-of examples of such an application is the groupware packet called Lotus.

Workflow and Administrative Management

Administrative management includes both workflow management and areas such as computer/telephony integration, where processes are defined and then automated. In these areas, users need not only to make processes more efficient, but also to reduce the cost of human agents. Much as in the messaging area, intelligent agents can be used to ascertain, then automate user wishes or business processes.

Mobile Access / Management

As computing becomes more pervasive and network centric computing shifts the focus from the desktop to the network, users want to be more mobile. Not only do they want to access network resources from any location, they want to access those resources despite bandwidth limitations of mobile technology such as wireless communication, and despite network volatility. Intelligent agents which (in this case) reside in the network rather than on the users' personal computers, can address these needs by persistently carrying out user requests despite network disturbances. In addition, agents can process data at its source and ship only compressed answers to the user, rather than overwhelming the network with large amounts of unprocessed data.

Information Access and Management

Information access and management is an area of great activity, given the rise in popularity of the Internet and the explosion of data available to users. It is the application area that this thesis will mainly focus on.Here, intelligent agents are helping users not only with search and filtering, but also with categorisation, prioritisation, selective dissemination, annotation, and (collaborative) sharing of information and documents.

LIMITATION OF INTELLIGENT AGENT

As with any technology-based solution, a number of limitations and concerns exist regarding the usage of intelligent agents.

No overall system controller

Intelligent agents may not be appropriate where there are global constraints that need to been forced, due to the fact that each agent is effectively acting independently of any central controller. Applications requiring real-time responses are also inappropriate.

No global perspective

An agent can only make decisions based on locally accumulated knowledge, therefore an agent might be missing the "big picture" of a problem domain.

Trusting delegation

A user of an intelligent agent is effectively giving responsibility of data acquisition and decision making to a piece of computer code, therefore they must be sure that they can trust the agent to carry out the delegated task with integrity.While some of these issues are technology related, others are side effects of the concept of intelligent agents itself. We cannot design an agent to be autonomous and capable of reaching its own decisions, only to decide that we now want to exert a central control over these agents,which is defeating the purpose of the concept

IMPACT OF INTELLIGENT AGENTS

Intelligent agents are innovative technologies that offer various benefits to their end users by automating complex or repetitive tasks. There are several potential organizational and cultural impacts of this technology that need to be considered. Organizational impacts include the transformation of the entire electronic commerce sector, operational encumbrance, and security overload. Software agents are able to quickly search the Internet, identify the best offers available online, and present this information to the end users in aggregate form. Users may not need to manually browse various websites of individual merchants; they are able to locate the best deal in a matter of seconds. This increases price-based competition and transforms the entire electronic commerce sector into a uniform perfect competition market. The cultural effects of the implementation of software agents include trust affliction, skills erosion, privacy attrition and social detachment. Some users may not feel entirely comfortable fully delegating important tasks to software applications. In order to act on a user’s behalf, a software agent needs to have a complete understanding of a user’s profile, including his/her personal preferences. This, in turn, may lead to unpredictable privacy issues. When users start relying on their software agents more, especially, for communication activities, they may lose contact with other human users and look at the word with the eyes of their agents.

INTELLIGENT INTERFACE

Intelligent interfaces specifically aim to enhance the flexibility, usability, and power of human-computer interaction for all users. In doing so, they exploit knowledge of users, tasks, tools, and content, as well as devices for supporting interaction within differing contexts of use.

REASONS FOR HAVING INTELLIEGENT INTERFACE

Why do we need intelligent interfaces? There are a couple of good reasons for wanting to create systems with intelligent interfaces:

Applications are becoming increasingly complex; users may need some guidance on how to use a particular part of a program, especially if the parts in question are rarely used or are confusing.

Applications are managing a lot of information. Often, there is too much information to display to the user. Techniques for determining what information is the most pertinent for a particular user is important so the user isn't overwhelmed with data.

As computers become more widely used in the workplace, more non-experts are finding themselves in front of systems which they don't fully understand. The assistance offered by intelligent interfaces might alleviate some problems and misunderstandings between computers and users.

Computers are being used in an increasing number of special or extreme situations, or are being used by special users. Examples of special or extreme situations include military programs, medical software, and programs in high-stress environments (such as distaster management). Intelligent interfaces would be needed in these situations because they can better provide for the user through the use of multimodal communication and knowledge of system functionality. Special users include primarily those with conditions that would otherwise prohibit them from effectively using a computer, such as people with visual or motor afflictions. Through multimodal communication and interface adaptability, intelligent interfaces can help make computers accessible to these users.

APPLICATION

There exist a lot of applications that work well without adding any kind of system "intelligence" applications where the computer is a mere tool, for a user that is well aware and capable of performing a specific task. We can compare this usage of the computer with the usage of a hammer: the hammer need not be intelligent, it suffices that it can be used by a user who can handle a hammer. Tools, typically, can be used in several ways, even to things that the original inventor did not think about; this requires a flexible and robust design but not any intelligence or adaptability built into the tool.

The main application areas for intelligent interfaces are thus such where the knowledge about how to solve a task partially resides with the computer system. Since the user does not know exactly what should be done, he or she cannot manipulate the computer as a tool, but must ask the system to do something for him or her. This request may be incomplete, vague or even incorrect given the user's real needs.

Some typical application areas that can be characterised this way are Intelligent tutoring, intelligent help and information filtering.

Intelligent Tutoring

 A "tutor" is a program that aims to give a personalised "education" to a user in a specific domain of knowledge .The tutor program may need to infer the user's understanding of the domain through analysing the user's performance on test problems. The advice can be given by actively intervening, and suggesting alternative courses of actions, or passively, by answering explicit user's queries. In both cases, the answers can be tailored to what the system perceives as the user's needs and misunderstandings. Passive tutoring is often done in the style of "critiquing", where the user first suggests a full solution and the system then judges this solution, points out errors and suggests alternative solutions.

Intelligent Help

 A "help" system aids a user in performing a specific task .Help is very similar to tutoring, but the main objective for a help system is to get something done, and not to make the learn something. Another difference is that many tutoring systems will lay out specific tasks for the user to do, in order to diagnose his or her misconceptions. A help system must act upon whatever information it can gather from the user's own choice of interactions with the system. A help system can either give help about the functionality of a computer program, or about some computer-independent task (repairing a car, for example). As with tutoring, help can be active or passive.

Information filtering

In open information sources such as the Internet, it is comparatively "cheap" to distribute information to a very large group of recipients. For recipients, this means that they are flooded with large masses of information, and find it hard to extract the information that is really relevant or interesting to them. Users need help in selecting the information that is relevant to them, but the problem is that they do not know what is out there. Information filtering techniques, and information retrieval in general, aim to find structure in the available information that can be used to aid users in navigating the information space and selecting the information that is relevant to themselves. The task is called "filtering" when the information space is rapidly changing. Information filtering tools may rely on text or image processing, but may also log the reading patterns of groups of users, to determine what kind of users are interested in a certain piece of information.

EXAMPLES

There are quite a few programs which use intelligent interfaces. Some of the more significant of these (those systems which are in actual use, as opposed to those written for the sole purpose of demonstrating IntInt techniques) include the following:

CUBRICON - This is a system used for Air Force command and control. It incorporates speech input and output, natural-language text, graphics, and pointing gestures by the user . The objective of using IntInt techniques in this system is to "simplify operator communication with sophisticated computer systems."

SAGE - This program creates intelligent data-graphics. The intelligent interfacing is in determining the best way to display a set of data so that the data is readable and understandable.

CHORIS - This system is designed to enable a wide range of users to interact effectively with varying types of complex systems [ref]. Its main strength lies in its knowledge of these complex systems.

UCEGO - the intelligent component of UNIX Consultant. This is a natural language system which helps the user solve problems encountered while using UNIX