Role Of Intelligent Agents

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An intelligent agent is a piece of software that acts for a user or other program in a relationship of agency. Such “action on behalf of” implies the authority to decide which action is appropriate .They work by allowing people to delegate work that they could have done to the agent software. Agents can, just as assis­tants can, automate repetitive tasks, remember things you forgot, intel­ligently summarize complex data, learn from you, and even make rec­ommendations to you.

Agents vs. Objects

Agents are more autonomous than objects.

Agents have flexible behavior, reactive, proactive, and social.

Agents have at least one thread of control but may have more.

Agents vs. Expert systems

Expert systems are not coupled to their environment;

Expert systems are not designed for reactive, proactive behavior.

Expert systems do not consider social ability

Intelligent Software Agents vs. Intelligent Agents in Artificial Intelligence

Intelligent agents are not just software programs but also be machines, human beings, and communities of human beings.

There are four types of intelligent software agents. They are:

Buyer agents also known as ‘shopping bots’, travel around a network (i.e. the internet) retrieving information and work very efficiently for commodity products such as CDs, books, electronic components, and other one-size-fits-all products. Amazon.com is a good example of a shopping bot.

User agents or personal agents are intelligent agents that take action on behalf of the user and perform the following tasks:

-Check e-mail, sort it according to the user’s order of preference, and alert when important emails arrive.

-Play computer games as opponent or patrol game areas

-Assemble customized news, data, and reports.

-Find information on the subject of our choice.

-Fill out forms on the Web automatically storing information for future reference

-Scan Web pages looking for and highlighting text

-Discuss topics ranging from deepest fears to sports

-Facilitate with online job search duties by scanning known job boards and sending the resume

-Profile synchronization across heterogeneous social networks.

Monitoring and Surveillance Agents are used to observe and report on equipment, usually computer systems. The agents may keep track of company inventory levels, observe competitors’ prices and relay them back to the company, watch stock manipulation by insider trading and rumors, etc.

A data mining agent operates in a data warehouse discovering information. A ‘data warehouse’ brings together information from lots of different sources. “Data mining” is the process of looking through the data warehouse to find information required to take action.

Intelligent agents can be grouped into five classes based on their degree of perceived intelligence and capability.

A simple reflex agent acts only on the basis of the current percept. The agent function is based on the condition-action rule: if condition then action. This agent function only succeeds when the environment is fully observable. Some reflex agents can also contain information on their current state which allows them to disregard conditions whose actuators are already triggered.

Model-based reflex agents can handle partially observable environments. Its current state is stored inside the agent maintaining some kind of structure which describes the part of the world which cannot be seen. This behavior requires information on how the world behaves and works. This additional information completes the “World View” model. He keeps track of the current state of the world using an internal model. It then chooses an action in the same way as the reflex agent.

Goal-based agents are model-based agents which store information regarding situations that are desirable. This allows the agent a way to choose among multiple possibilities, selecting the one which reaches a goal state.

Utility-based agents only distinguish between goal states and non-goal states. It is possible to define a measure of how desirable a particular state is. This measure can be obtained through the use of a utility function which maps a state to a measure of the utility of the state.

Learning agents Learning has an advantage that it allows the agents to initially operate in unknown environments and to become more competent than its initial knowledge alone might allow.

Some of the sub-agents that may be a part of an Intelligent Agent are:

Decision Agents -geared to decision making

Input Agents– process and make sense of sensor inputs

Processing Agents– solve a problem like speech recognition

Spatial Agents– relate to the physical real-world

World Agents– incorporate a combination of all the other classes of agents

Believable agents – An agent exhibiting a personality via artificial character Physical Agents – percept through sensors and act through actuators.

Temporal Agents – offer instructions or data acts to a computer program or human being and takes program inputs.

CHARACTERISTICS OF INTELLIGENT AGENTS

Accommodate new problem solving rules incrementally

Adapt online and in real time

Be able to analyze itself in terms of behavior, error and success.

Learn and improve through interaction with the environment

Learn quickly from large amounts of data

Have memory-based exemplar storage and retrieval capacities

Have parameters to represent short and long term memory.

VALUE OF INTELLIGENT AGENTS IN A NETWORKED WORLD

A major value of employing software agents with intranet, internet, and extranet applications is that they are able to assist in locating and filtering data. They save time by making decisions about what is relevant to the user. They are able to sort through the network and the various databases effortlessly and with unswerving attention to detail in order to extract the best data. Agents are artificial intelligence’s answer to a need created by internet-worked computers. The main reasons for growth of this technology are:

Mundane personal activity: In a fast-paced society, time-strapped people need new ways to minimize the time spent on routine personal tasks and to devote more time to professional activities.

Search and retrieval: It is not possible to directly manipulate a distrib­uted database system containing millions of data objects. Users relegate the task to agents who will perform the tedious, time-consuming, and repetitive tasks of searching databases, retrieving and filtering information, and delivering it back to the user.

Repetitive office work: There is a need to automate tasks performed by administrative and clerical personnel in functions like sales or customer support in order to reduce labour costs and increase office productivity.

Decision support: There is a need for increased support for tasks performed by knowledge workers who should take timely and knowledgeable decisions to increase their effectiveness.

Domain experts: It is advisable to model costly expertise and make it widely available. Expert software agents could model real-world agents such as translators, lawyers, diplomats, union negotiators, stockbro­kers.

The list of tasks performed by these agents includes advising, alerting, broadcasting, browsing, critiquing, distributing, enlisting, empowering, explaining, filtering, guiding, identifying, matching, monitoring, navigating, negotiating, organizing, presenting, querying, reminding, reporting, retrieving, scheduling, searching, securing, soliciting, sorting, storing, suggesting, summarizing, teaching, translating ,watching and so on.

Overall, software agents make the networked world less forbidding, save time by reducing the effort required to locate and retrieve data, and improve productivity by off-loading a variety of mundane, tedious, and mindless tasks.

ESSENTIALS OF INTELLIGENT AGENTS

There are several possible traits or abilities that people think of when they discuss intelligent agents. Four of these traits—autonomy, temporal continuity, reactivity, and goal driven—are essential to distinguish agents from other types of software objects, programs, or systems. Software agents possessing only these traits are often labeled simple or weak. Besides these essential traits, a software agent may also possess additional traits such as adaptability, mobility, sociability, and personality.

Autonomy: Regular computer programs respond only to direct manipulation. In contrast, an intelligent agent senses its environment and acts autonomously upon it. He can initiate communication, monitor events, and perform tasks without the direct intervention of humans or others.

Temporal Continuity: An intelligent agent is a program to which a user assigns a goal or task. The idea is that once a task or goal has been delegated, it is up to the agent to work tirelessly in pursuit of that goal. An agent continues to run—either actively in the foreground or sleeping in the background—monitoring system events that trigger its actions.

Reactivity: An n intelligent agent responds in a timely fashion to changes in its environment. This characteristic is crucial for delegation and automation.

Goal Driven: An n intelligent agent does more than simply respond to changes in its environment. It can accept high-level requests specifying the goals of a human user and decide how and where to satisfy the requests.

IMPACTS 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.

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