Management information system (1)

Chapter 1
Information as a Key Resource

Three aspects to information
 Data vs Information
 Personal dimension of information
 Organizational dimension of information

Data vs information
• Data refers to the lowest abstract or a raw input which when processed or arranged makes
meaningful output. It is the group or chunks which represent quantitative and qualitative
attributes pertaining to variables. Information is usually the processed outcome of data. More
specifically speaking, it is derived from data. Information is a concept and can be used in many
domains.
Business Intelligence
(BI) is a broad category of computer software solutions that enables a company or organization to gain
insight into its critical operations through reporting applications and analysis tools.

Tabular Form

Chart

Dashboard
Dimensions of information

Personal Dimensions of Information
Time Dimension
 Having access to information when you need it
 Having information that describes the time period your considering
 Location Dimension

 having access to information no matter where you are. Ideally, in other words, your location or
the information’s location should not matter. You should be able to access information in a
hotel room, at home, in the student center of your campus.
Form Dimension
 Having information in a form most useable
 Free of errors

Organizational Dimension of information
 information flows
 information granularity
Information flows
Information granularity

People as Key Resource

Information and Technology Literacy
Key Points:
 Technology is important today because information is important.
 Technology is a set of tools for working with information. If we didn’t need to work with
information, we would have little use for technology.
 So, it’s important to know how to work with technology so you can better work with
information.

Key Term:
 Technology- literate knowledge worker - a person who knows how and when to apply
technology.
 - can define what information they need, know how and where to obtain that information,
understand the information once they receive it, and can act appropriately based on the
information to help the organization achieve the greatest advantage.
 Ethics - the principles and standards that guide our behaviour toward other people.
 Hacker - a very knowledgeable computer user who uses his or her knowledge to invade other
people’s computers.
Information Technology as a key Resource

Information Technology
- Branch of engineering that deals with the use of computers to store, retrieve and transmit information.
Ubiquitous Computing
• Decentralized Computing - is the allocation of resources both hardware and software to each
individual workstation or office location.

• Shared Information - Traditional information sharing referred to one-to-one exchanges of data
between a sender and reliever.
• Mobile Computing - Is a human-computer interaction by which a computer is expected to be
transported during normal usage.

Creating Business Vision for Information Technology

Ethics, Security and Privacy

Four Categories of Ethical Issues
• Privacy Issues
• Accuracy Issues
• Property Issues
• Accessibility Issues

Key Information Security Terms
• Threat
• Exposure
• Vulnerability
• Risk
• Information system controls

Threats to Privacy
• Electronic Surveillance
• Personal Information in Databases
• Information on Internet Bulletin Boards, Newsgroups, and Social Networking Sites

Decision Support And Artificial Intelligence :
Brain power for your Business

Types of Decisions You Face

 Structured decision – processing a certain information in a specified way so that you will always
get the right answer
 Nonstructured decision – one for which there may be several “right” answers, without a sure
way to get the right answer
 Recurring decision – one that happens repeatedly
 Nonrecurring (ad hoc) decision – one you make infrequently

B. Decision Support System

A decision support system (DSS) is a computer-based information system that supports business or
organizational decision-making activities. It is a collection of integrated software applications and
hardware that form the backbone of an organization’s decision making process. DSSs serve the
management, operations, and planning levels of an organization and help to make decisions, which may
be rapidly changing and not easily specified in advance.

DSSs include knowledge-based systems. A properly designed DSS is an interactive software-based
system intended to help decision makers compile useful information from a combination of raw data,
documents, and personal knowledge, or business models to identify and solve problems and make
decisions.

Typical information that a decision support application might gather and present includes:

inventories of information assets (including legacy and relational data sources, cubes, data
warehouses, and data marts),
comparative sales figures between one period and the next,
projected revenue figures based on product sales assumptions.

Components of a decision support system

1. database (or knowledge base),

A database is an organized collection of data, usually in digital form. Data in the database are
typically organized to model relevant aspects of reality (for example, the availability of rooms in
hotels), in a way that supports processes requiring this information (for example, finding a hotel

with vacancies). The system that organizes, stores and provides access to the data is called a
database system. In technical usage, the term may be narrowed to specify particular aspects of
organized collection of data and may refer to the logical database, to the physical database as
data content in computer data storage or to many other database sub-definitions.

2. model (i.e., the decision context and user criteria)

A model is anything used in any way to represent anything else. Some models are physical
objects, for instance, a toy model which may be assembled, and may even be made to work like
the object it represents. The term conceptual model may be used to refer to models which are
formed after a conceptualization process in the mind. Conceptual models represent human
intentions or semantics.

3. user interface.

The user interface, in the industrial design field of human–machine interaction, is the space where
interaction between humans and machines occurs. The goal of interaction between a human and a
machine at the user interface is effective operation and control of the machine, and feedback from the
machine which aids the operator in making operational decisions. Examples of this broad concept of
user interfaces include the interactive aspects of computer operating systems, hand tools, heavy
machinery operator controls, and process controls. The design considerations applicable when creating
user interfaces are related to or involve such disciplines as ergonomics and psychology.

A user interface is the system by which people (users) interact with a machine. The user interface
includes hardware (physical) and software (logical) components. User interfaces exist for various
systems, and provide a means of:

Input, allowing the users to manipulate a system
Output, allowing the system to indicate the effects of the users' manipulation

4. Users
A user is an agent, either a human agent (end-user) or software agent, who uses a computer or
network service. A user often has a user account and is identified by a username (also user
name). Other terms for username include login name, screen name (also screen name),
nickname (also nick), or handle, which is derived from the identical Citizen's Band radio term.

C. Geographic Information System

A geographic information system is a system designed to capture, store, manipulate, analyze, manage,
and present all types of geographical data. The acronym GIS is sometimes used for geographical
information science or geospatial information studies to refer to the academic discipline or career of

working with geographic information systems. In the simplest terms, GIS is the merging of cartography,
statistical analysis, and database technology. A geographic information system (GIS) integrates
hardware, software, and data for capturing, managing, analyzing, and displaying all forms of
geographically referenced information.

A GIS can be thought of as a system—it digitally creates and "manipulates" spatial areas that may be
jurisdictional, purpose, or application-oriented. Generally, a GIS is custom-designed for an organization.
Hence, a GIS developed for an application, jurisdiction, enterprise, or purpose may not be necessarily
interoperable or compatible with a GIS that has been developed for some other application, jurisdiction,
enterprise, or purpose.

In a general sense, the term describes any information system that integrates, stores, edits, analyzes,
shares, and displays geographic information for informing decision making.

GIS allows us to view, understand, question, interpret, and visualize data in many ways that reveal
relationships, patterns, and trends in the form of maps, globes, reports, and charts.

A GIS helps you answer questions and solve problems by looking at your data in a way that is quickly
understood and easily shared.

GIS technology can be integrated into any enterprise information system framework.

Artificial intelligence is a branch of computer science which aims at building machines that can think,
feel and take decisions just like humans do. Before discussing its future prospects, let's understand
exactly what artificial Intelligence is all about.

In the area of robotics, computers are now widely used in assembly plants, but they are capable only of
very limited tasks. Robots have great difficulty identifying objects based on appearance or feel, and they
still move and handle objects clumsily.

Artificial Intelligence (AI) is the area of computer science focusing on creating machines that can engage
on behaviours that humans consider intelligent. The ability to create intelligent machines has intrigued
humans since ancient times and today with the advent of the computer and 50 years of research into AI
programming techniques, the dream of smart machines is becoming a reality. Researchers are creating
systems which can mimic human thought, understand speech, beat the best human chess player, and
countless other feats never before possible. Find out how the military is applying AI logic to its hi-tech
systems, and how in the near future Artificial Intelligence may impact our lives.
Currently, no computers exhibit full artificial intelligence (that is, are able to simulate human behaviour).
The greatest advances have occurred in the field of games playing. The best computer chess programs

are now capable of beating humans. In May, 1997, an IBM super-computer called Deep Blue defeated
world chess champion Gary Kasparov in a chess match.

AI research is highly technical and specialized, deeply divided into subfields that often fail to
communicate with each other.[5] Some of the division is due to social and cultural factors: subfields
have grown up around particular institutions and the work of individual researchers. AI research is also
divided by several technical issues. There are subfields which are focussed on the solution of specific
problems, on one of several possible approaches, on the use of widely differing tools and towards the
accomplishment of particular applications. The central problems of AI include such traits as reasoning,
knowledge, planning, learning, communication, perception and the ability to move and manipulate
objects.[6] General intelligence (or "strong AI") is still among the field's long term goals.[7] Currently
popular approaches include statistical methods, computational intelligence and traditional symbolic AI.
There are an enormous number of tools used in AI, including versions of search and mathematical
optimization, logic, methods based on probability and economics, and many others.

The field was founded on the claim that a central property of humans, intelligence—the sapience of
Homo sapiens—can be so precisely described that it can be simulated by a machine.[8] This raises
philosophical issues about the nature of the mind and the ethics of creating artificial beings, issues
which have been addressed by myth, fiction and philosophy since antiquity.[9] Artificial intelligence has
been the subject of optimism,[10] but has also suffered setbacks[11] and, today, has become an
essential part of the technology industry, providing the heavy lifting for many of the most difficult
problems in computer science.[12]

Artificial intelligence (AI) is the intelligence of machines and the branch of computer science that aims
to create it. AI textbooks define the field as "the study and design of intelligent agents “where an
intelligent agent is a system that perceives its environment and takes actions that maximize its chances
of success. John McCarthy, who coined the term in 1955, defines it as "the science and engineering of
making intelligent machines."


Picture sample of ARTIFICIAL INTELLICENCE

An expert system is a computer program that simulates the judgement and behaviour of a human or an
organization that has expert knowledge and experience in a particular field. Typically, such a system
contains a knowledge base containing accumulated experience and a set of rules for applying the
knowledge base to each particular situation that is described to the program. Sophisticated expert
systems can be enhanced with additions to the knowledge base or to the set of rules.

In artificial intelligence, an expert system is a computer system that emulates the decision-making
ability of a human expert. Expert systems are designed to solve complex problems by reasoning about
knowledge, like an expert, and not by following the procedure of a developer as is the case in
conventional programming. The first expert systems were created in the 1970s and then proliferated in
the 1980s. Expert systems were among the first truly successful forms of AI software
An expert system has a unique structure, different from traditional programs. It is divided into two
parts, one fixed, independent of the expert system: the inference engine, and one variable: the
knowledge base. To run an expert system, the engine reasons about the knowledge base like a human.
In the 80s a third part appeared: a dialog interface to communicate with users. This ability to conduct a
conversation with users was later called "conversational".

NEURAL NETWORKS

• Neural network (artificial neural network or ANN) – an artificial intelligence system that is
capable of finding and differentiating patterns
• in simple term it can be used to help us predict future movement in the company

Neural Networks Can…

 Learn and adjust to new circumstances on their own
 Take part in massive parallel processing
 Function without complete information
 Cope with huge volumes of information
 Analyze nonlinear relationships

Fuzzy logic

-is a form of many-valued logic or probabilistic logic; it deals with reasoning that is approximate rather
than fixed

Genetic Algorithm

 an artificial intelligence system that mimics the evolutionary, survival-of-the-fittest process to
generate increasingly better solutions to a problem
 is routinely used to generate useful solutions to optimization and search problems

Evolutionary Principles of Genetic Algorithms

1. Selection – or survival of the fittest or giving preference to better outcomes
2. Crossover – combining portion of good outcomes to create even better outcomes
3. Mutation – randomly trying combinations and evaluating the success of each

Genetic Algorithms Can…

 Take thousands or even millions of possible solutions and combining and recombining them
until it finds the optimal solution

intelligent agent

 Intelligent agent – software that assists you, or acts on your behalf, in performing repetitive
computer-related tasks
› Buyer agents or shopping bots
› User or personal agents
› Monitoring-and surveillance agents

› Data-mining agents

An intelligent agent is software that assists people and act on their behalf. Intelligent agents work by
allowing people to delegate work that they could have done, to the agent software. Agents can perform
repetitive tasks, remember things you forgot, intelligently summarize complex data, learn from you and
even make recommendations to you.

Two types of intelligent agent

 Buyer agent or shopping bot – an intelligent agent on a Web sites that helps you, the customer,
find products and services you want

Simple reflex agents
Simple reflex agents act only on the basis of the current percept, ignoring the rest of the percept history.
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.
Infinite loops are often unavoidable for simple reflex agents operating in partially observable
environments. Note: If the agent can randomize its actions, it may be possible to escape from infinite
loops.
Model-based reflex agents
A model-based agent can handle a partially observable environment. 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 knowledge about "how the world works" is called a model of the world, hence the name
"model-based agent".
Goal-based agents
Goal-based agents further expand on the capabilities of the model-based agents, by using "goal"
information. Goal information describes 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
Goal-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. The most important distinction is

between the "learning element", which is responsible for making improvements, and the "performance
element", which is responsible for selecting external actions.

Tools & Languages used to implement Intelligent Agent

There are many tools and languages used to implement intelligent agent and here are some of the tools
and languages listed below:

Aglet, which is programming code that, can be transported along with state information. Aglets are Java
objects that can move from one host on the Internet to another.

Facile, which is a high-level, higher-order programming language for systems that require a combination
of complex data manipulation and concurrent and distributed computing. It combines Standard ML
(SML), with a model of higher-order concurrent proc esses based on CCS. Facile is being used at ECRC to
develop Mobile Service Agents.

Penguin, which is a Perl 5 module that provides a set of functions to (1) send encrypted, digitally signed
Perl code to a remote machine to be executed; and (2) receive code and, depending on who signed it,
execute it in an arbitrarily secure, limited compartment.

Python, which is an interpreted, interactive, object-oriented programming language.

Information Agent

An individual or a business entity that has the task of providing explanations of various transactions of
another party to relevant persons who need to know the information

What are Information Agents?

An information agent is a computational software entity (an intelligent agent) that may access one or
multiple, distributed, and heterogeneous information sources available, and pro-actively acquires,
mediates, and maintains relevant information on behalf of its user(s) or other agents preferably just-in-
time. In other words, information agents are supposed to cope with the difficulties associated with the
information overload of the user. This implies their ability to semantically broker information by:

(1) providing a pro-active resource discovery;
(2) resolving the information impedance of information consumers and providers;
(3) offering value-added information services and products to the user or other agents.
Monitoring-and-surveillance (predictive) agents

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 rumours, etc.
service monitoring

User agent

Possible privacy issue
As with many other HTTP request headers, the information in the "User-Agent" string contributes to the
information that the client sends to the server, since the string can vary considerably from user to
user.[3]
User agents, or personal agents, are intelligent agents that take action on your behalf. In this category
belong those intelligent agents that already perform, or will shortly perform, the following tasks:

* Check your e-mail, sort it according to the user’s order of preference, and alert you when important
emails arrive.
* Play computer games as your opponent or patrol game areas for you.
* Assemble customised news reports for you. There are several versions of these, including newshub
and CNN.
* Find information for you on the subject of your choice (portal search).
* Fill out forms on the Web automatically for you, storing your information for future reference
* Scan Web pages looking for and highlighting text that constitutes the “important” part of the
information there
* “Discuss” topics with you ranging from your deepest fears to sports
* Facilitate with online job search duties by scanning known job boards and sending the resume to
opportunities who meet the desired criteria (CRM solution)
* Profile synchronisation across heterogeneous social networks

Data mining agents

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 (CRM support).
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 that you can use to take action, such as ways to increase sales or
keep customers who are considering defecting.

Decision Support And Artificial Intelligence :
Brain power for your Business

Types of Decisions You Face

 Structured decision – processing a certain information in a specified way so that you will always
get the right answer
 Nonstructured decision – one for which there may be several “right” answers, without a sure
way to get the right answer
 Recurring decision – one that happens repeatedly
 Nonrecurring (ad hoc) decision – one you make infrequently

B. Decision Support System

A decision support system (DSS) is a computer-based information system that supports business or
organizational decision-making activities. It is a collection of integrated software applications and
hardware that form the backbone of an organization’s decision making process. DSSs serve the
management, operations, and planning levels of an organization and help to make decisions, which may
be rapidly changing and not easily specified in advance.

DSSs include knowledge-based systems. A properly designed DSS is an interactive software-based
system intended to help decision makers compile useful information from a combination of raw data,
documents, and personal knowledge, or business models to identify and solve problems and make
decisions.

Typical information that a decision support application might gather and present includes:

inventories of information assets (including legacy and relational data sources, cubes, data
warehouses, and data marts),
comparative sales figures between one period and the next,
projected revenue figures based on product sales assumptions.

Components of a decision support system

5. database (or knowledge base),

A database is an organized collection of data, usually in digital form. Data in the database are
typically organized to model relevant aspects of reality (for example, the availability of rooms in
hotels), in a way that supports processes requiring this information (for example, finding a hotel
with vacancies). The system that organizes, stores and provides access to the data is called a
database system. In technical usage, the term may be narrowed to specify particular aspects of
organized collection of data and may refer to the logical database, to the physical database as
data content in computer data storage or to many other database sub-definitions.

6. model (i.e., the decision context and user criteria)

A model is anything used in any way to represent anything else. Some models are physical
objects, for instance, a toy model which may be assembled, and may even be made to work like
the object it represents. The term conceptual model may be used to refer to models which are
formed after a conceptualization process in the mind. Conceptual models represent human
intentions or semantics.

7. user interface.

The user interface, in the industrial design field of human–machine interaction, is the space where
interaction between humans and machines occurs. The goal of interaction between a human and a
machine at the user interface is effective operation and control of the machine, and feedback from the
machine which aids the operator in making operational decisions. Examples of this broad concept of
user interfaces include the interactive aspects of computer operating systems, hand tools, heavy
machinery operator controls, and process controls. The design considerations applicable when creating
user interfaces are related to or involve such disciplines as ergonomics and psychology.

A user interface is the system by which people (users) interact with a machine. The user interface
includes hardware (physical) and software (logical) components. User interfaces exist for various
systems, and provide a means of:

Input, allowing the users to manipulate a system
Output, allowing the system to indicate the effects of the users' manipulation

8. Users
A user is an agent, either a human agent (end-user) or software agent, who uses a computer or
network service. A user often has a user account and is identified by a username (also user
name). Other terms for username include login name, screen name (also screen name),
nickname (also nick), or handle, which is derived from the identical Citizen's Band radio term.

C. Geographic Information System

A geographic information system is a system designed to capture, store, manipulate, analyze, manage,
and present all types of geographical data. The acronym GIS is sometimes used for geographical
information science or geospatial information studies to refer to the academic discipline or career of
working with geographic information systems. In the simplest terms, GIS is the merging of cartography,
statistical analysis, and database technology. A geographic information system (GIS) integrates
hardware, software, and data for capturing, managing, analyzing, and displaying all forms of
geographically referenced information.

A GIS can be thought of as a system—it digitally creates and "manipulates" spatial areas that may be
jurisdictional, purpose, or application-oriented. Generally, a GIS is custom-designed for an organization.
Hence, a GIS developed for an application, jurisdiction, enterprise, or purpose may not be necessarily
interoperable or compatible with a GIS that has been developed for some other application, jurisdiction,
enterprise, or purpose.

In a general sense, the term describes any information system that integrates, stores, edits, analyzes,
shares, and displays geographic information for informing decision making.

GIS allows us to view, understand, question, interpret, and visualize data in many ways that reveal
relationships, patterns, and trends in the form of maps, globes, reports, and charts.

A GIS helps you answer questions and solve problems by looking at your data in a way that is quickly
understood and easily shared.

GIS technology can be integrated into any enterprise information system framework.


In the area of robotics, computers are now widely used in assembly plants, but they are capable only of
very limited tasks. Robots have great difficulty identifying objects based on appearance or feel, and they
still move and handle objects clumsily.

Artificial Intelligence (AI) is the area of computer science focusing on creating machines that can engage
on behaviours that humans consider intelligent. The ability to create intelligent machines has intrigued

humans since ancient times and today with the advent of the computer and 50 years of research into AI
programming techniques, the dream of smart machines is becoming a reality. Researchers are creating
systems which can mimic human thought, understand speech, beat the best human chess player, and
countless other feats never before possible. Find out how the military is applying AI logic to its hi-tech
systems, and how in the near future Artificial Intelligence may impact our lives.
Currently, no computers exhibit full artificial intelligence (that is, are able to simulate human behaviour).
The greatest advances have occurred in the field of games playing. The best computer chess programs
are now capable of beating humans. In May, 1997, an IBM super-computer called Deep Blue defeated
world chess champion Gary Kasparov in a chess match.

AI research is highly technical and specialized, deeply divided into subfields that often fail to
communicate with each other.[5] Some of the division is due to social and cultural factors: subfields
have grown up around particular institutions and the work of individual researchers. AI research is also
divided by several technical issues. There are subfields which are focussed on the solution of specific
problems, on one of several possible approaches, on the use of widely differing tools and towards the
accomplishment of particular applications. The central problems of AI include such traits as reasoning,
knowledge, planning, learning, communication, perception and the ability to move and manipulate
objects.[6] General intelligence (or "strong AI") is still among the field's long term goals.[7] Currently
popular approaches include statistical methods, computational intelligence and traditional symbolic AI.
There are an enormous number of tools used in AI, including versions of search and mathematical
optimization, logic, methods based on probability and economics, and many others.

The field was founded on the claim that a central property of humans, intelligence—the sapience of
Homo sapiens—can be so precisely described that it can be simulated by a machine.[8] This raises
philosophical issues about the nature of the mind and the ethics of creating artificial beings, issues
which have been addressed by myth, fiction and philosophy since antiquity.[9] Artificial intelligence has
been the subject of optimism,[10] but has also suffered setbacks[11] and, today, has become an
essential part of the technology industry, providing the heavy lifting for many of the most difficult
problems in computer science.[12]

Artificial intelligence (AI) is the intelligence of machines and the branch of computer science that aims
to create it. AI textbooks define the field as "the study and design of intelligent agents “where an
intelligent agent is a system that perceives its environment and takes actions that maximize its chances
of success. John McCarthy, who coined the term in 1955, defines it as "the science and engineering of
making intelligent machines."


Picture sample of ARTIFICIAL INTELLICENCE

An expert system is a computer program that simulates the judgement and behaviour of a human or an
organization that has expert knowledge and experience in a particular field. Typically, such a system
contains a knowledge base containing accumulated experience and a set of rules for applying the
knowledge base to each particular situation that is described to the program. Sophisticated expert
systems can be enhanced with additions to the knowledge base or to the set of rules.

In artificial intelligence, an expert system is a computer system that emulates the decision-making
ability of a human expert. Expert systems are designed to solve complex problems by reasoning about
knowledge, like an expert, and not by following the procedure of a developer as is the case in
conventional programming. The first expert systems were created in the 1970s and then proliferated in
the 1980s. Expert systems were among the first truly successful forms of AI software
An expert system has a unique structure, different from traditional programs. It is divided into two
parts, one fixed, independent of the expert system: the inference engine, and one variable: the
knowledge base. To run an expert system, the engine reasons about the knowledge base like a human.
In the 80s a third part appeared: a dialog interface to communicate with users. This ability to conduct a
conversation with users was later called "conversational".

NEURAL NETWORKS

• Neural network (artificial neural network or ANN) – an artificial intelligence system that is
capable of finding and differentiating patterns
• in simple term it can be used to help us predict future movement in the company

Neural Networks Can…

 Learn and adjust to new circumstances on their own
 Take part in massive parallel processing
 Function without complete information
 Cope with huge volumes of information
 Analyze nonlinear relationships

Fuzzy logic

-is a form of many-valued logic or probabilistic logic; it deals with reasoning that is approximate rather
than fixed

Genetic Algorithm

 an artificial intelligence system that mimics the evolutionary, survival-of-the-fittest process to
generate increasingly better solutions to a problem
 is routinely used to generate useful solutions to optimization and search problems

Evolutionary Principles of Genetic Algorithms

4. Selection – or survival of the fittest or giving preference to better outcomes
5. Crossover – combining portion of good outcomes to create even better outcomes
6. Mutation – randomly trying combinations and evaluating the success of each

Genetic Algorithms Can…

 Take thousands or even millions of possible solutions and combining and recombining them
until it finds the optimal solution

intelligent agent

 Intelligent agent – software that assists you, or acts on your behalf, in performing repetitive
computer-related tasks

› Buyer agents or shopping bots
› User or personal agents
› Monitoring-and surveillance agents
› Data-mining agents

An intelligent agent is software that assists people and act on their behalf. Intelligent agents work by
allowing people to delegate work that they could have done, to the agent software. Agents can perform
repetitive tasks, remember things you forgot, intelligently summarize complex data, learn from you and
even make recommendations to you.

Two types of intelligent agent

 Buyer agent or shopping bot – an intelligent agent on a Web sites that helps you, the customer,
find products and services you want

Simple reflex agents
Simple reflex agents act only on the basis of the current percept, ignoring the rest of the percept history.
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.
Infinite loops are often unavoidable for simple reflex agents operating in partially observable
environments. Note: If the agent can randomize its actions, it may be possible to escape from infinite
loops.
Model-based reflex agents
A model-based agent can handle a partially observable environment. 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 knowledge about "how the world works" is called a model of the world, hence the name
"model-based agent".
Goal-based agents
Goal-based agents further expand on the capabilities of the model-based agents, by using "goal"
information. Goal information describes 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
Goal-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. The most important distinction is
between the "learning element", which is responsible for making improvements, and the "performance
element", which is responsible for selecting external actions.

Tools & Languages used to implement Intelligent Agent

There are many tools and languages used to implement intelligent agent and here are some of the tools
and languages listed below:

Aglet, which is programming code that, can be transported along with state information. Aglets are Java
objects that can move from one host on the Internet to another.

Facile, which is a high-level, higher-order programming language for systems that require a combination
of complex data manipulation and concurrent and distributed computing. It combines Standard ML
(SML), with a model of higher-order concurrent proc esses based on CCS. Facile is being used at ECRC to
develop Mobile Service Agents.

Penguin, which is a Perl 5 module that provides a set of functions to (1) send encrypted, digitally signed
Perl code to a remote machine to be executed; and (2) receive code and, depending on who signed it,
execute it in an arbitrarily secure, limited compartment.

Python, which is an interpreted, interactive, object-oriented programming language.

Information Agent

An individual or a business entity that has the task of providing explanations of various transactions of
another party to relevant persons who need to know the information

What are Information Agents?

An information agent is a computational software entity (an intelligent agent) that may access one or
multiple, distributed, and heterogeneous information sources available, and pro-actively acquires,
mediates, and maintains relevant information on behalf of its user(s) or other agents preferably just-in-
time. In other words, information agents are supposed to cope with the difficulties associated with the
information overload of the user. This implies their ability to semantically broker information by:

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 (CRM support).
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 that you can use to take action, such as ways to increase sales or
keep customers who are considering defecting.

What is Electronic Commerce?

Commonly known as e-commerce or e-comm, is the buying and selling of products or services
over electronic systems such as the Internet and other computer networks.

E-Commerce Business Models

1. Business to consumer (B2C):

The B2C model sells goods or services to the consumer, generally using online catalog
and shopping cart transaction systems.

EXAMPLE: Amazon

2. Business to business (B2B):

Companies doing business with each other such as manufacturers selling to distributors
and wholesalers selling to retailers. Pricing is based on quantity of order and is often negotiable.

EXAMPLEs: Cisco
intranet services
web meetings

3. Consumer to business (C2B):
Consumers offer products and services to companies and the companies pay them.

EXAMPLE: Google AdSense

4. Consumer to consumer (C2C):
Consumers can post classified ads or offers to sell their property to other consumers.
This offers some protection for consumers allowing them the chance to take advantage
of the prices offered by motivated sellers.

EXAMPLE: e-Bay

Understand your business, Products, Services and Customers

Who are your Customers?

Internet users
Online buyer

What is the value of your products and services as perceived by your customer?

Value

Quality of Product
Services
Expectations

Dimensions of Quality

• Performance -Product characteristics.

 Availability
 Reliability

• Features -Secondary characteristics of a product.

• Warranty - Public promise of quality product supported by a guarantee of customer satisfaction.

• Price - Value of prouct.

Find Customers and Establish Relationships

5 Key Ways to Build Customer Relationships

1. Build your network--it's your sales lifeline. Your network includes business
colleagues, professional acquaintances, prospective and existing customers, partners, suppliers,
contractors and association members, as well as family, friends and people you meet at school,
church and in your community.

2. Communication is a contact sport, so do it early and often. Relationships have a
short shelf life. No matter how charming, enthusiastic or persuasive you are, no one will likely
remember you from a business card or a one-time meeting. One of the biggest mistakes people
make is that they come home from networking events and fail to follow up. Make the
connection immediately. Send a "nice to meet you" e-mail or let these new contacts know

you've added them to your newsletter list and then send them the latest copy. Immediately
reinforce who you are, what you do and the connection you've made.

3. E-mail marketing keeps relationships strong on a shoestring budget. Build your
reputation as an expert by giving away some free insight. You have interesting things to say! An
easy way to communicate is with a brief e-mail newsletter that shows prospects why they
should buy from you. For just pennies per customer, you can distribute an e-mail newsletter
that includes tips, advice and short items that entice consumers and leave them wanting more.
E-mail marketing is a cost-effective and easy way to stay on customers' minds, build their
confidence in your expertise, and retain them. And it's viral: Contacts and customers who find
what you do interesting or valuable will forward your e-mail message or newsletter to other
people, just like word of mouth marketing.

4. Reward loyal customers, and they'll reward you. According to global management
consulting firm Bain and Co., a 5 percent increase in retention yields profit increases of 25 to
100 percent. And on average, repeat customers spend 67 percent more than new customers. So
your most profitable customers are repeat customers. Are you doing enough to encourage them
to work with you again? Stay in touch, and give them something of value in exchange for their
time, attention and business. It doesn't need to be too much; a coupon, notice of a special
event, helpful insights and advice, or news they can use are all effective. Just remember: If you
don't keep in touch with your customers, your competitors will.

5. Loyal customers are your best salespeople. So spend the time to build your network and
do the follow-up. Today there are cost effective tools, like e-mail marketing, that make this easy.
You can e-mail a simple newsletter, an offer or an update message of interest to your network
(make sure it's of interest to them, not just to you). Then they'll remember you and what you do and
deliver value back to you with referrals. They'll hear about opportunities you'll never hear about.
The only way they can say, "Wow, I met somebody who's really good at XYZ. You should give her a
call," is if they remember you. Then your customers become your sales force.

* Business to Consumer

1. Communicate frequently

2. Offer customer rewards

3. Enhance customer service

* Business to Business

1.Create a Database
2. Improve with time

3. Be prompt with inquiries
Example:
Pocketcents
MOVE MONEY EASILY & SECURELY
B2C Payment Systems
Credit cards
Financial cybermediaries
Electronic checks
Electronic Bill Presentment and Payment
Smart cards

B2C Payment Systems
Must move money and other information such as shipping address
Digital wallets can help
Digital wallet – software and information
Software provides transaction security
Information includes delivery information and other forms of necessary information

B2B Payment Systems
Business customers…
Make large purchases
Will not pay with credit card or financial cybermediary
Use financial EDI
Pay for many purchases at once (perhaps the end of the month)

Security: The Pervading Concern
Security is very important when moving money
Some security measures…
Encryption
Secure Sockets Layers
Secure Electronic Transactions
Many, many others

The Broadening of E-government

E-government
E-governance is the application of information and communication technology (ICT) for
delivering services, exchange of information communication transaction, integration various stand-one
system and services between government-to-citizens (G2C), government-to-business (G2B),
government-to-government (G2G) as well as back office processes and interactions within the entire
government framework.

Advantages
 Democratization
 Environmental bonuses
 Speed, efficiency, and convenience
 Public approval

Disadvantages
 Hyper-surveillance
 Cost
 Inaccessibility
 False sense of transparency and accountability

 Government to Government (G2G)
Government to government (G2G) is the electronic sharing of data and/or information
systems between government agencies, departments or organizations. The goal of G2G is to
support e-government initiatives by improving communication, data access and data sharing.

Example: NEGIS (Northeast Gang Information System)

 Government to Business (G2B)
Government-to-Business (G2B) is the online non-commercial interaction between local and
central government and the commercial business sector, rather than private individuals (G2C), with
the purpose of providing businesses information and advice on e-business 'best practices'.

 Government to Citizens (G2C)
Government-to-Citizen (G2C) is the communication link between a government and private
individuals or residents. Such G2C communication most often refers to that which takes place
through Information and Communication Technologies (ICTs), but can also include direct mail and
media campaigns. G2C can take place at the federal, state, and local levels. G2C stands in contrast to
G2B, or Government-Business networks.

 International Government to Government
Most member states have developed their own national E-Government strategy to develop
their national E-Government projects. The level of ”maturity” of every strategy is strictly related to
speciﬁc national factors, like the ﬁnancial resources, the internet penetration, the eLiteracy of the
population, the organizational form or even their constitutional morphology.

 Government Spending Information Technology
Responsible for state-wide IT planning, coordination, and initiatives.

Ex. http://www.azgita.gov/

Management information system (1)

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