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Artificial Intelligence
Chapter 1 - Part 2
Artificial Intelligence
(605451)
Dr.Hassan Al-Tarawneh
What is Artificial Intelligence?
• Artificial Intelligence (AI) is a branch of
computer science devoted to creating
computer software and hardware to
attempt to mimic human intelligence or
human intelligent behaviour
What is Intelligent Behavior?
• Learn from experience
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Respond flexibly in situation that are
New or not anticipated
Ambiguous (not clearly defined)
Specified by contradictory information
• Apply ‘learnt’ or ‘programmed’ knowledge to
solve problems
• Use reasoning in solving problem
• Understand and infer facts and rules
• Recognize the relative importance of different
elements in a situation
What is AI concerned with?
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Mainly AI is concerned with two basic
ideas:
1. It involves studying the thought
processes of humans to understand what
intelligence is.
2. It deals with representing thought
processes using computers to create
artificially intelligent entities for testing
the theories of intelligence.
Some Definition of AI
• AI is a term that compasses many definitions:
– “The goal of work in AI is to build machines that
performs tasks normally requiring human intelligence”
– N. Nilsson
– “The goals of AI research is to construct computer
programs which exhibit behaviors that we call
intelligent behavior when we observe it in human
beings – E. Feigenbaum & J. Feldman
– “AI is the science of making computers smart. It is
practiced both by those who want to make computers
more useful and by those who want to understand the
nature of intelligence” – Patrick H. Winston
Some Definition of AI
• “AI is the ability of machines to do things that
people would require intelligence.
• AI research is an attempt to discover and
describe aspects of human intelligence that can
be simulated by machines.
• Alternatively, AI research may be viewed as an
attempt to develop an mathematical theory to
describe the abilities and actions of things
(natural or man-made) exhibiting ‘intelligent’
behavior and server as a calculus for the design
of intelligent machines“ – Philip C. Jackson
Artificial Intelligence vs Natural Intelligence
AI Advantages
AI offers ease of duplication and
dissemination of knowledge
Natural Intelligence Disadvantage
Knowledge duplication and transfer
of expertise requires apprenticeship
AI offers more permanent storage of Natural Intelligence is perishable –
knowledge
people forget or be inaccessible
AI being a computer technology is
consistent, thorough and formal
Natural Intelligence can be erratic as
that is the way most people are
AI can be documented – decisions
made by the system can be easily
introspected and documented
Natural Intelligence is difficult to
document - people may do things
but can not explain how they did it
AI, from a commercial point of view,
is less expensive - a given system
may be bought only once and used
frequently
Experts having knowledge of a
certain domain are more expensive
Natural Intelligence vs Artificial
Intelligence
Natural Intelligence
Advantages
AI Disadvantage
Natural Intelligence is creative
– the ability to acquire
knowledge is inherent in
humans
AI systems have a static
knowledge, they work with
only the programmed
knowledge
Natural intelligence work with
sensory experience
AI system can work with only
symbolic input
Humans have the natural
ability to reason, which is
applicable to a wide context
of experience
AI system have a very limited
scope and can reason to a
limited extend based on the
reasoning mechanism
implemented
Comparing Humans and
Computers
• Computer are good at
– Processing large amount of data
– Storing (permanently) and retrieve large
amount of data
– Working at extremely fast speeds
– Doing extensive arithmetic calculation with
great accuracy
– Working for long periods without fatigue
Comparing Humans and
Computers
• Humans are good at
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Recognizing various things, either seen before or not
Recognizing the relationship patterns between things
Thinking – common sense reasoning
Combining all types of sensory inputs
Acting appropriately in novel situations
Learning new things and changing behavior patterns
Making decisions even when given incomplete
information
– Working with noisy, incomplete or ambiguous
information
Comparing Humans and
Computers
• The tasks humans do naturally however
are extremely difficult for a computer
program to accomplish
• If computers are to be termed as
intelligent, they must be able to do the
same kind of task as humans do naturally
AI in Practice
• AI is an combination of many different sciences and
technologies:
• Linguistics
– Computational linguistics
– Phycholinguistics
– Socio - linguistics
• Phychology
– Cognitive science
– Phycholinguistics
• Philosophy
– Logic
– Philosophy of mind
– Philosophy of language
• Electrical Engineering
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Image processing
Speech processing
Pattern recognition
Robotics
Machine learning
Neural networks
• Optimization
– Scheduling
• Management
– Management information system
– Decision making
AI in Practice
• AI provides the framework and methodology for several
growing commercial technologies
• Expert System
– Computerized advisory and/or decision making systems that
attempt to imitate the reasoning process and knowledge of
experts in solving domain-specific problems
• Natural Language Processing
– Natural language technology attempts to give computer users
the ability to communicate with computer in natural language.
Also deals with understanding textual language for various
applications
• Speech recognition
– The recognition of spoken language by a computer – breaking
up of speech into meaningful units, i.e. words
AI in Practice
• Robotics and Sensory Systems
– Combining robots having mechanical motions with sensory
system to produce machines of varying intelligence and abilities.
Here a robot senses its environment and modifies its behavior
on the basis of the information gained.
• Computer vision and scene recognition
– To understand digitized visual information received from a
sensor and then making a decision – interpreting a visual scene
• Intelligent Computer-Aides Instruction
– To develop machines that can tutor humans in the interactive
manner. Such systems have a vast knowledge base and are
used for teaching problems solving skills, simulations, discovery
and learning, drill and proactive and so on.
AI in Practice
• Game playing
– To develop intelligent programs that can play games
such as chess
• Neural network
– Systems that attempt to mimic the neural structure of
the human brain. Information processing is carried out
in a manner close to that of the human brain
• Intelligent Databases – data mining
– Intelligently managing large databases, facilitating the
furnishing of complex queries and automatically
gleaning hidden information from databases – data
mining
AI in Practice
• Exemplar Systems
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Language translation systems
Speech to text system
Air traffic control systems
Automates personal systems
Supervisory systems
Intelligent highways – traffic monitoring
Robots for hazardous conditions
Expert system for law, medicine
Neural network based forecasting – finance, stocks, medicine
Executive summary producing systems
Automatic programming
Summarizing news from papers
Intelligent design – architecture, mechanical and electrical systems
Chess playing systems – deep blue
Medical diagnostic systems
AI in Practice
• AI is a subject of scientific investigation,
with the following working practices :
– Researchers construct theories about what AI
programs are capable of and test them with
mathematical analysis or experiments
– This may involve decision making and
problem solving using symbolic processing. A
symbol is a string of characters that stands for
some real-world concept