Artificial Intelligence

WALCHAND INSTITUTE OF TECHNOLOGY

A PAPER PRESENTATION ON:

Artificial Intelligence
By

Author’s: Abbas Hashmi Sushant Gore

Class: T.E. CSE T.E CSE

E-mail: abbas.hashmi5@gmail.com sushantgore04@gmail.com

Ph. No.: 9096265578 9028585925

Rcpt. No.: SOL6-40 SOL7-21

Guided by:

Prof. M.A.Mahant

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Abstract :

Artificial intelligence (AI) is a field of computer science It is expected that the robots in future, will take on
that explores computational models of problem solving, everybody's work. Whether it is office work or the work
where the problems to be solved are of the complexity of at home, robots will accomplish it even faster and
problems solved by human beings. Artificial Intelligence efficiently than human beings. So if somebody's falling ill,
is the study of how to make computers do things which, at they can obtain a robot nurse who will give periodic
the moment, people do better. It is the intelligence of medicines to them. How much care, concern and empathy
machines and the branch of computer science that aims to the robot nurse will have towards the patient is anybody's
create it. The study and design of intelligent agents is also guess!
called as Artificial Intelligence. The central problems of
AI include such traits as reasoning, knowledge, planning, This paper intends to study the techniques
learning, communication, perception and the ability to developed in artificial intelligence (AI) from the
move and manipulate objects. standpoint of their applications in all fields related to
engineering. In particular, it focuses on techniques
This paper elaborates the new approaches to AI. developed (or that are being developed) in artificial
Artificial intelligence in the future will churn out intelligence that can be deployed in solving problems
machines and computers, which are much more associated with distinct processes. This paper highlights a
sophisticated than the ones that we have today. comparative study between approaches and its
applications.

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Introduction: relationships? And what about perception and
comprehension? Research into the areas of learning, of
The term artificial intelligence was first coined in 1956, at language, and of sensory perception have aided scientists in
the Dartmouth conference, and since then Artificial building intelligent machines. One of the most
Intelligence has expanded because of the theories and challenging approaches facing experts is building systems
principles developed by its dedicated researchers. Artificial that mimic the behavior of the human brain, made up of
Intelligence (AI) is the area of computer science focusing on billions of neurons, and arguably the most complex matter in
creating machines that can engage on behaviors that humans the universe. Perhaps the best way to gauge the intelligence
consider intelligent. In 1957, the first version of a new of a machine is British computer scientist Alan Turing's test.
program The General Problem Solver (GPS) was tested. The He stated that a computer would deserves to be called
program developed by the same pair which developed the intelligent if it could deceive a human into believing that it
Logic Theorist. The GPS was an extension of Wiener's was human.
feedback principle, and was capable of solving a greater
extent of common sense problems. During the 1970's Many new methods in the development
of AI were tested, notably Minsky's frames theory. Also
David Marr proposed new theories about machine vision, for
example, how it would be possible to distinguish an image
based on the shading of an image, basic information on
shapes, color, edges, and texture. With analysis of this
information, frames of what an image might be could then be
referenced. another development during this time was the
PROLOGUE language. The language was proposed for In
1972.

During the 1980's AI was moving at a faster pace, and
further into the corporate sector. In 1986, US sales of AI-
related hardware and software surged to $425 million. Expert
systems in particular demand because of their efficiency.
Companies such as Digital Electronics were using XCON, an
expert system designed to program the large VAX computers.
Fig 1: Artificial Intelligence
DuPont, General Motors, and Boeing relied heavily on expert
systems Indeed to keep up with the demand for the computer
The ability to create intelligent machines has intrigued
experts, companies such as Teknowledge and Intellicorp
humans since ancient times and today with the advent of the
specializing in creating software to aid in producing expert
computer and 50 years of research into AI programming
systems formed. Other expert systems were designed to find
techniques, the dream of smart machines is becoming a
and correct flaws in existing expert systems.
reality. Researchers are creating systems which can mimic
human thought, understand speech, beat the best human chess We have been studying this issue of AI application for
player, and countless other feats never before possible. Find quite some time now and know all the terms and facts. But
out how the military is applying AI logic to its hi-tech what we all really need to know is what can we do to get our
systems, and how in the near future Artificial Intelligence hands on some AI today. How can we as individuals use our
may impact our lives. AI is a combination of computer own technology? We hope to discuss this in depth (but as
science, physiology, and philosophy. AI is a broad topic, briefly as possible) so that you the consumer can use AI as it
consisting of different fields, from machine vision to expert is intended.
systems. The element that the fields of AI have in common is
the creation of machines that can "think". In order to classify First, we should be prepared for a change. Our
machines as "thinking", it is necessary to define intelligence. conservative ways stand in the way of progress. AI is a new
To what degree does intelligence consist of, for example, step that is very helpful to the society. Machines can do jobs
solving complex problems, or making generalizations and that require detailed instructions followed and mental

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alertness. AI with its learning capabilities can accomplish When access to digital computers became possible in the
those tasks but only if the worlds conservatives are ready to middle 1950s, AI research began to explore the possibility
change and allow this to be a possibility. It makes us think that human intelligence could be reduced to symbol
about how early man finally accepted the wheel as a good manipulation.
invention, not something taking away from its heritage or
tradition. Cognitive simulation -

Secondly, we must be prepared to learn about the Economist Herbert Simon and Alan Newell studied human
capabilities of AI. The more use we get out of the machines problem solving skills and attempted to formalize them, and
the less work is required by us. In turn less injuries and stress their work laid the foundations of the field of artificial
to human beings. Human beings are a species that learn by intelligence, as well as cognitive science, operations research
trying, and we must be prepared to give AI a chance seeing and management science. Their research team performed
AI as a blessing, not an inhibition. psychological experiments to demonstrate the similarities
between human problem solving and the programs (such as
Finally, we need to be prepared for the worst of AI. their "General Problem Solver") they were developing. This
Something as revolutionary as AI is sure to have many kinks tradition, centered at Carnegie Mellon University, would
to work out. There is always that fear that if AI is learning eventually culminate in the development of the Soar
based, will machines learn that being rich and successful is a architecture in the middle 80s.
good thing, then wage war against economic powers and
famous people? There are so many things that can go wrong When computers with large memories became available
with a new system so we must be as prepared as we can be around 1970, researchers from all three traditions began to
for this new technology. build knowledge into AI applications. This "knowledge
revolution" led to the development and deployment of expert
However, even though the fear of the machines are there, systems (introduced by Edward Feigenbaum), the first truly
their capabilities are infinite Whatever we teach AI, they will successful form of AI software. The knowledge revolution
suggest in the future if a positive outcome arrives from it. AI was also driven by the realization that truly enormous of
are like children that need to be taught to be kind, well amounts knowledge would be required by many simple AI
mannered, and intelligent. If they are to make important applications.

COMPUTATION :
decisions, they should be wise. We as citizens need to make
sure AI programmers are keeping things on the level. We NEURAL NETWORKS AND PARALLEL
should be sure they are doing the job correctly, so that no
future accidents occur. The human brain is made up of a web of billions of cells
called neurons, and understanding its complexities is seen as
Description: one of the last frontiers in scientific research. It is the aim of
AI researchers who prefer this bottom-up approach to
Artificial Intelligence is concerned with the study and construct electronic circuits that act as neurons do in the
creation of computer systems that exhibit some form of human brain. Although much of the working of the brain
intelligence and attempts to apply such knowledge to the remains unknown, the complex network of neurons is what
design of computer based systems that can understand a gives humans intelligent characteristics. By itself, a neuron is
natural language or understanding of natural intelligence. In
the following we will see the different approaches and
techniques in the software engineering.

APPROACHES:

CYBERNETICS AND BRAIL SIMULATION :

Fig 2:The neuron "firing", passing a signal to the
Traditional Symbolic AI -
next in the chain.

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not intelligent, but when grouped together, neurons are able systems had the potential to interpret statistics, in order to
to pass electrical signals through networks. formulate rules. An expert system works much like a
detective solves a mystery. Using the information, and logic
Research has shown that a signal received by a neuron or rules, an expert system can solve the problem. For
travels through the dendrite region, and down the axon. example it the expert system was designed to distinguish
Separating nerve cells is a gap called the synapse. In order for birds it may have the following as shown in Fig 3.
the signal to be transferred to the next neuron, the signal must
be converted from electrical to chemical energy. The signal ARTIFICIAL INTELLIGENCE TECHNIQUES IN
can then be received by the next neuron and processed. SOFTWARE ENGINEERING (AITSE):
Software Engineering is a knowledge-intensive activity,
Warren McCulloch after completing medical school at
requiring extensive knowledge of the application domain and
Yale, along with Walter Pitts a mathematician proposed a
of the target software itself. Many Software products costs
hypothesis to explain the fundamentals of how neural
can be attributed to the ineffectiveness of current techniques
networks made the brain work. Based on experiments with
for managing this knowledge, and Artificial Intelligence
neurons, McCulloch and Pitts showed that neurons might be
techniques can help alleviate this situation.
considered devices for processing binary numbers. An
important back of mathematic logic, binary numbers
(represented as 1's and 0's or true and false) were also the
basis of the electronic computer. This link is the basis of
computer-simulated neural networks, also know as parallel
computing.

A century earlier the true / false nature of binary numbers
was theorized in 1854 by George Boole in his postulates
concerning the Laws of Thought. Boole's principles make up
what is known as Boolean algebra, the collection of logic
concerning AND, OR, NOT operands.

TOP DOWN APPROACHES :
Because of the large storage capacity of computers, expert Fig 4:Traditional software development
process.

The traditional view of software development process
begins at the requirements specification and ends at testing
the software. At each of these stages, different kinds of
knowledge (design knowledge at design stage and
programming and domain knowledge at the coding stage) are
required. At each of the two stages: design and coding, exist a
cycle: error recognition and error correction. Experience
shows that errors can occur at any stage of software
development. Errors due to coding may occur because of
faulty design. Such errors are usually expensive to correct.

A basic problem of software engineering is the long delay
between the requirements specification and the delivery of a
product. This long development cycle causes requirements to
change before product arrival. In addition, there is the
problem of phase independence of requirements, design and
Fig 3: Charts like these represent the logic of expert
codes. Phase independence means that any decision made at
systems. Using a similar set of rules, experts can have a
variety of applications. With improved interfacing,

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one level becomes fixed for the next level. Thus, the coding The Risk Management process is a method of identifying
team is forced to recode whenever there is change in design. risks in advance and establishing methods of avoiding those
risks and /or reducing the impact of those risks should they
Expert system use knowledge rather than data to control occur. The process of risk management begins during the
the solution process. Knowledge engineers build systems by analysis phase of software development life cycle. However,
eliciting knowledge from experts, coding, that knowledge in the actual process of managing risks continues throughout the
an appropriate form, validating the knowledge, and ultimately product development phase. The given Figure displays the
constructing a system using a variety of building tools. The steps of the risk management process. Formally, articulated,
main phases the expert system development processes are:- risk management process consists of three steps:

• Planning
• Knowledge acquisition and analysis
• Knowledge design Risk management strategies utilize lot of developer time
• Code and in software development phases there is a link between
• Knowledge verification
• System evaluation all the phases by introducing a isolation phase among the
phases we can reduce the time in development by revisiting
each phase after changes in requirements. By using AI based
systems with the help of automated tool or automated
programming tool we can eliminate risk assessment phase
saving our time in software development. Because of AITSE
we can reduce the development time in software
development. Coding phase in software development process
can be changed into Genetic Code.

Fig 5: Expert System development. Applications:

Current Usage:

Fig 6: Risk Management Process.

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 There are many applications of artificial Understanding natural language
intelligence at present. Some of them have been
listed here. Just getting a sequence of words into a computer is not
 Banks and other financial institutions rely on enough. Parsing sentences is not enough either. The computer
intelligent software, which provide accurate analysis has to be provided with an understanding of the domain the
of the data and helps make predictions based upon text is about, and this is presently possible only for very
that data. limited domains.
 Stocks and commodities are being traded without
Computer vision
any human interference - all thanks to the intelligent
systems. The world is composed of three-dimensional objects, but
 Artificial intelligence is used for weather the inputs to the human eye and computers' TV cameras are
forecasting. two dimensional. Some useful programs can work solely in
 It is used by airlines to keep a check on its system. two dimensions, but full computer vision requires partial
 Robotics is the greatest success story, in the field of three-dimensional information that is not just a set of two-
artificial intelligence. Spacecrafts are send by NASA dimensional views. At present there are only limited ways of
and other space organizations into space, which are representing three-dimensional information directly, and they
completely manned by robots. Even some are not as good as what humans evidently use.
manufacturing processes are now being completely
undertaken by robots. Robots are being used in Expert systems
industrial processes, that are dangerous to human
beings, such as in nuclear power plants. A ``knowledge engineer'' interviews experts in a certain
 Usage of artificial intelligence is quite evident in domain and tries to embody their knowledge in a computer
various speech recognition systems, such as IBM program for carrying out some task. How well this works
ViaVoice software and Windows Vista. depends on whether the intellectual mechanisms required for
the task are within the present state of AI. When this turned
out not to be so, there were many disappointing results. One
Game playing of the first expert systems was MYCIN in 1974, which
diagnosed bacterial infections of the blood and suggested
You can buy machines that can play master level chess for treatments. It did better than medical students or practicing
a few hundred dollars. There is some AI in them, but they doctors, provided its limitations were observed. Namely, its
play well against people mainly through brute force ontology included bacteria, symptoms, and treatments and
computation--looking at hundreds of thousands of positions. did not include patients, doctors, hospitals, death, recovery,
To beat a world champion by brute force and known reliable and events occurring in time. Its interactions depended on a
heuristics requires being able to look at 200 million positions single patient being considered. Since the experts consulted
per second. by the knowledge engineers knew about patients, doctors,
death, recovery, etc., it is clear that the knowledge engineers
Speech recognition
forced what the experts told them into a predetermined
In the 1990s, computer speech recognition reached a framework. In the present state of AI, this has to be true. The
practical level for limited purposes. Thus United Airlines has usefulness of current expert systems depends on their users
replaced its keyboard tree for flight information by a system having common sense.
using speech recognition of flight numbers and city names. It
Heuristic classification
is quite convenient. On the the other hand, while it is possible
to instruct some computers using speech, most users have One of the most feasible kinds of expert system given the
gone back to the keyboard and the mouse as still more present knowledge of AI is to put some information in one of
convenient. a fixed set of categories using several sources of information.
An example is advising whether to accept a proposed credit
card purchase. Information is available about the owner of
the credit card, his record of payment and also about the item

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he is buying and about the establishment from which he is will they do it with dedication? Will they work with
buying it (e.g., about whether there have been previous credit devotion? How will intelligent machines work
card frauds at this establishment). wholeheartedly when they don’t have a heart?
Apart from these concerns, there are chances that intelligent
Advantages : machines overpower human beings. Machines may enslave
human beings and start ruling the world. Imagine artificial
While we already deal with some virtual AI -- notably in
intelligence taking over human intellect! The picture is
action games against computer-controlled "bots" or
definitely not rosy.
challenging a computer opponent to chess -- the work of
Novamente, Electric Sheep Company and other firms has the Some thinkers consider it ethically wrong to create
potential to initiate a new age of virtual AI, one where, for artificial intelligent machines. According to them,
better or worse, humans and artificial intelligences could intelligence is God’s gift to mankind. It is not correct to even
potentially be indistinguishable. try to recreate intelligence. It is against ethics to create
replicas of human beings. Don’t you also think so.
If you think about it, we take in numerous pieces of
information just walking down the street, much of it The ultimate goal of research in AI and Robotics is to
unconsciously. You might be thinking about the weather, the produce an android which can interact meaningfully with
pace of your steps, where to step next, the movement of other human beings. A huge amount of research effort is being
people, smells, sounds, the distance to the destination, the exerted in order to achieve this aim and a lot of progress has
effect of the environment around you and so forth. An already been made. Researchers have manufactured androids
artificial intelligence in a virtual world has fewer of these that can walk on two legs, that can climb stairs, that can grasp
variables to deal with because as of yet, no virtual world objects without breaking or dropping them, that can recognise
approaches the complexity of the real world. It may be that faces and a variety of physical objects, that can imitate what
by simplifying the world in which the artificial intelligence they see human beings doing and so on. It is hard to make
operates (and by working in a self-contained world), some robots that can do these things and I have no desire to belittle
breakthroughs can be achieved. Such a process would allow the scientific achievements that have already been made, but
for a more linear development of artificial intelligence rather even if a robot succeeds in doing all these things as well as a
than an attempt to immediately jump to lifelike robots human being it will still lack at least one essential human
capable of learning, reason and self-analysis. ability, namely that of learning from other people by
accepting what they say and by believing what they have
Limitations: written. The ultimate goal of AI cannot be achieved until we
have implemented in a computer system the ability to acquire
If robots start replacing human resources in every field, we
information from testimony.
will have to deal with serious issues like unemployment in
turn leading to mental depression, poverty and crime in the A number of people, who should know better , make
society. Human beings deprived of their work life may not predictions about when AI will achieve its ultimate goal.
find any means to channelize their energies and harness their There is no possibility of AI succeeding in the foreseeable
expertise. Human beings will be left with empty time. future. People who say otherwise are simply ignorant of the
state of research into testimony. AI cannot succeed until an
Secondly, replacing human beings with robots in every
android (or computer program) can evaluate testimony in a
field may not be a right decision to make. There are many
similar way to that in which a human being can.
jobs that require the human touch. Intelligent machines will
surely not be able to substitute for the caring behavior of Conclusion:
hospital nurses or the promising voice of a doctor. Intelligent
machines may not be the right choice for customer service. Technology is neither good nor bad. It never has been.
What man does with it is another story entirely.
One of the major disadvantages of intelligent machines is
Technological changes are certainly coming. They are
that they cannot be ‘human’. We might be able to make them
already taking place. They are constant and ubiquitous. Many
think. But will we be able to make them feel? Intelligent
believe that they are accelerating. They are probably also
machines will definitely be able to work for long hours. But

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unstoppable. Just as with the scientific knowledge that went Bibliography:
into making the atomic bomb, once it is possible to do
something, someone will eventually do it. 1. Luger, George & Stubblefield, William (2004),
Artificial Intelligence: Structures and Strategies for
Artificial intelligence has successfully been used in a wide Complex Problem Solving (5th ed.), The
range of fields including medical diagnosis, stock trading, Benjamin/Cummings Publishing Company, Inc., pp.
robot control, law, scientific discovery and toys. Frequently, 720.
when a technique reaches mainstream use it is no longer
considered artificial intelligence. 2. http://electronics.howstuffworks.com/artificial-
intelligence-second-life1.htm
These rivaling theories have lead researchers in one of two
basic approaches; bottom-up and top-down. Bottom-up 3. http://electronics.howstuffworks.com/artificial-
theorists believe the best way to achieve artificial intelligence intelligence-second-life1.htm
is to build electronic replicas of the human brain's complex
4. Artificial Intelligence in Perspective By Daniel
network of problems, or making generalizations and
Gureasko Bobrow - Science – 1994.
relationships.
5. Artificial Intelligence: A Modern Approach: By
One of the most challenging approaches facing experts is
Stuart Jonathan Russell, Peter Norvig - Computers -
building systems that mimic the behavior of the human brain,
2003 - 1132 pages.
made up of billions of neurons.

Artificial intelligence has successfully been used in a wide
range of fields including medical diagnosis, stock trading,
robot control, law, scientific discovery and toys. Frequently,
when a technique reaches mainstream use it is no longer
considered artificial intelligence.

In the quest to create intelligent machines, the field of
Artificial Intelligence has split into several different
approaches based on the opinions about the most promising
methods and theories neurons, while the top-down approach
attempts to mimic the brain's behavior with computer
programs.

The more use we get out of the machines the less work is
required by us. In turn less injuries and stress to human
beings. Human beings are a species that learn by trying, and
we must be prepared to give AI a chance seeing AI as a
blessing, not an inhibition.

In conclusion, in some fields such as forecasting weather
or finding bugs in computer software, expert systems are
sometimes more accurate than humans. But for other fields,
such as medicine, computers aiding doctors will be
beneficial, but the human doctor should not be replaced.
Expert systems have the power and range to aid to benefit,
and in some cases replace humans, and computer experts, if
used with discretion, will benefit human kind.

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