ITT63 ARTIFICIAL INTELLIGENCE UNIT 1
Academic Year 2016-2017(EVEN SEM)
Introduction: History of AI - Intelligent agents – structure of agents and its functions - problem
spaces and search- Heuristic Search techniques –Best-first search- Problem reduction-
Constraintsatisfaction-Means Ends Analysis.
INTRODUCTION
WHAT IS ARTIFICIAL INTELLIGENCE?
Artificial Intelligence is a branch of computer science that deals with the creation of computer
programs that can provide solutions, otherwise human would have to solve.
Artificial Intelligence definitions are given on the basis of
(i) Based on thought process and reasoning.
(ii) Based on the behaviour.
(iii) Based on human performance.
(iv) Based on Rationality.
Views of AI fall into four categories:
Thinking humanly
Thinking rationally
“The automation of activities that we “ The study of mental faculties
associate with human thinking, through the use of computational
activities such as decision-making, models”
problem solving, learning…”
Acting humanly Acting rationally
“The study of how to make computers “Computational intelligence is
do things at which, at the moment, the study of the design of
people are better” intelligent agents”
Acting humanly: Turing Test
• The Turing Test, Proposed by Alan Turing (1950) ,was designed to provide a satisfactory
operational definition of Intelligence ."Computing machinery and intelligence":
III YR /VI SEM Page 1
,ITT63 ARTIFICIAL INTELLIGENCE UNIT 1
• "Can machines think?" "Can machines behave intelligently?"
• Operational test for intelligent behavior: The Imitation Game
• Predicted that by 2000, a machine might have a 30% chance of fooling a person for 5 minutes
• Anticipated all major arguments against AI in following 50 years
• Suggested major components of AI: knowledge, reasoning, language understanding, learning.
Turing test
•Three rooms contain a person, a computer, and an interrogator.
•The interrogator can communicate with the other two by teleprinter.
•The interrogator tries to determine which the person is and which the machine is.
•The machine tries to fool the interrogator into believing that it is the person.
•If the machine succeeds, then we conclude that the machine can think.
The computer would need to possess the following capabilities:
Natural language processing to enable it to communicate successfully in English.
Knowledge representation to store what it knows or hears;
Automated reasoning to use the stored information to answer questions and to draw new
conclusions.
Machine learning to adapt to new circumstances and to detect and extrapolate patterns.
Computer vision to perceive objects.
Robotics to manipulate objects and move about.
Thinking humanly: cognitive modeling
• In 1960’s "cognitive revolution": information-processing psychology
• Requires scientific theories of internal activities of the brain
III YR /VI SEM Page 2
,ITT63 ARTIFICIAL INTELLIGENCE UNIT 1
• How to validate? Requires
1) Predicting and testing behaviour of human subjects (top-down)
2) Direct identification from neurological data (bottom-up)
• Both approaches (roughly, Cognitive Science and Cognitive Neuroscience) are now distinct from
Artificial Intelligence
Try to understand how the mind works. How do we think?
Two possible routes to find answers:
By introspection: We figure it out ourselves!
By experiment: Draw upon techniques of psychology to conduct controlled experiments. (Rat
in a box!)
Thinking rationally: "laws of thought"
• Aristotle: what are correct arguments/thought processes?
• Several Greek schools developed various forms of logic: notation and rules of derivation for
thoughts; may or may not have proceeded to the idea of mechanization
• Direct line through mathematics and philosophy to modern AI
• Problems:
– Not all intelligent behaviour is mediated by logical deliberation
– What is the purpose of thinking? What thoughts should I have?
Trying to understand how we actually think is one route to AI. But how about how we should
think.
Use logic to capture the laws of rational thought as symbols.
Reasoning involves shifting symbols according to well-defined rules (like algebra).
Result is idealized reasoning.
Acting rationally: rational agent
• Rational behaviour: doing the right thing
• The right thing: that which is expected to maximize goal achievement, given the available
information
III YR /VI SEM Page 3
, ITT63 ARTIFICIAL INTELLIGENCE UNIT 1
• Doesn't necessarily involve thinking – e.g., blinking reflex – but thinking should be in the service
of rational action
Rational agents
• An agent is an entity that perceives and acts
• This course is about designing rational agents
• Abstractly, an agent is a function from percept histories to actions:
[f: P* A]
• For any given class of environments and tasks, we seek the agent (or class of agents) with the best
performance.
• Caveat: computational limitations make perfect rationality unachievable.
Design best program for given machine resources.
FOUNDATIONS OF ARTIFICIAL INTELLIGENCE
PHILOSHOPY
Aristotle (384-322 B.C.) was the first to formulate a precise set of laws governing the rational
part of the mind. He developed an informal system of syllogisms for proper reasoning, which in
principle allowed one to generate conclusions mechanically, given initial premises.
Thomas Hobbes (1588-1679) proposed that reasoning was like numerical computation that "we add and
subtract in our silent thoughts." The automation of computation itself was already well under way. The
first known calculating machine was constructed around 1623 by the German scientist. The idea of a set
of rules that can describe the formal, rational part of the mind, the next step is to consider the mind as a
physical system.
MATHEMATICS
Philosophers staked out most of the important ideas of k1, but the leap to a formal science
required a level of mathematical formalization in three fundamental areas: logic, computation, and
probability. The idea of formal logic can be traced back to the philosophers of ancient Greece, but its
mathematical development really began with the work of George Boole who worked out the details of
propositional, or Boolean.
III YR /VI SEM Page 4
Academic Year 2016-2017(EVEN SEM)
Introduction: History of AI - Intelligent agents – structure of agents and its functions - problem
spaces and search- Heuristic Search techniques –Best-first search- Problem reduction-
Constraintsatisfaction-Means Ends Analysis.
INTRODUCTION
WHAT IS ARTIFICIAL INTELLIGENCE?
Artificial Intelligence is a branch of computer science that deals with the creation of computer
programs that can provide solutions, otherwise human would have to solve.
Artificial Intelligence definitions are given on the basis of
(i) Based on thought process and reasoning.
(ii) Based on the behaviour.
(iii) Based on human performance.
(iv) Based on Rationality.
Views of AI fall into four categories:
Thinking humanly
Thinking rationally
“The automation of activities that we “ The study of mental faculties
associate with human thinking, through the use of computational
activities such as decision-making, models”
problem solving, learning…”
Acting humanly Acting rationally
“The study of how to make computers “Computational intelligence is
do things at which, at the moment, the study of the design of
people are better” intelligent agents”
Acting humanly: Turing Test
• The Turing Test, Proposed by Alan Turing (1950) ,was designed to provide a satisfactory
operational definition of Intelligence ."Computing machinery and intelligence":
III YR /VI SEM Page 1
,ITT63 ARTIFICIAL INTELLIGENCE UNIT 1
• "Can machines think?" "Can machines behave intelligently?"
• Operational test for intelligent behavior: The Imitation Game
• Predicted that by 2000, a machine might have a 30% chance of fooling a person for 5 minutes
• Anticipated all major arguments against AI in following 50 years
• Suggested major components of AI: knowledge, reasoning, language understanding, learning.
Turing test
•Three rooms contain a person, a computer, and an interrogator.
•The interrogator can communicate with the other two by teleprinter.
•The interrogator tries to determine which the person is and which the machine is.
•The machine tries to fool the interrogator into believing that it is the person.
•If the machine succeeds, then we conclude that the machine can think.
The computer would need to possess the following capabilities:
Natural language processing to enable it to communicate successfully in English.
Knowledge representation to store what it knows or hears;
Automated reasoning to use the stored information to answer questions and to draw new
conclusions.
Machine learning to adapt to new circumstances and to detect and extrapolate patterns.
Computer vision to perceive objects.
Robotics to manipulate objects and move about.
Thinking humanly: cognitive modeling
• In 1960’s "cognitive revolution": information-processing psychology
• Requires scientific theories of internal activities of the brain
III YR /VI SEM Page 2
,ITT63 ARTIFICIAL INTELLIGENCE UNIT 1
• How to validate? Requires
1) Predicting and testing behaviour of human subjects (top-down)
2) Direct identification from neurological data (bottom-up)
• Both approaches (roughly, Cognitive Science and Cognitive Neuroscience) are now distinct from
Artificial Intelligence
Try to understand how the mind works. How do we think?
Two possible routes to find answers:
By introspection: We figure it out ourselves!
By experiment: Draw upon techniques of psychology to conduct controlled experiments. (Rat
in a box!)
Thinking rationally: "laws of thought"
• Aristotle: what are correct arguments/thought processes?
• Several Greek schools developed various forms of logic: notation and rules of derivation for
thoughts; may or may not have proceeded to the idea of mechanization
• Direct line through mathematics and philosophy to modern AI
• Problems:
– Not all intelligent behaviour is mediated by logical deliberation
– What is the purpose of thinking? What thoughts should I have?
Trying to understand how we actually think is one route to AI. But how about how we should
think.
Use logic to capture the laws of rational thought as symbols.
Reasoning involves shifting symbols according to well-defined rules (like algebra).
Result is idealized reasoning.
Acting rationally: rational agent
• Rational behaviour: doing the right thing
• The right thing: that which is expected to maximize goal achievement, given the available
information
III YR /VI SEM Page 3
, ITT63 ARTIFICIAL INTELLIGENCE UNIT 1
• Doesn't necessarily involve thinking – e.g., blinking reflex – but thinking should be in the service
of rational action
Rational agents
• An agent is an entity that perceives and acts
• This course is about designing rational agents
• Abstractly, an agent is a function from percept histories to actions:
[f: P* A]
• For any given class of environments and tasks, we seek the agent (or class of agents) with the best
performance.
• Caveat: computational limitations make perfect rationality unachievable.
Design best program for given machine resources.
FOUNDATIONS OF ARTIFICIAL INTELLIGENCE
PHILOSHOPY
Aristotle (384-322 B.C.) was the first to formulate a precise set of laws governing the rational
part of the mind. He developed an informal system of syllogisms for proper reasoning, which in
principle allowed one to generate conclusions mechanically, given initial premises.
Thomas Hobbes (1588-1679) proposed that reasoning was like numerical computation that "we add and
subtract in our silent thoughts." The automation of computation itself was already well under way. The
first known calculating machine was constructed around 1623 by the German scientist. The idea of a set
of rules that can describe the formal, rational part of the mind, the next step is to consider the mind as a
physical system.
MATHEMATICS
Philosophers staked out most of the important ideas of k1, but the leap to a formal science
required a level of mathematical formalization in three fundamental areas: logic, computation, and
probability. The idea of formal logic can be traced back to the philosophers of ancient Greece, but its
mathematical development really began with the work of George Boole who worked out the details of
propositional, or Boolean.
III YR /VI SEM Page 4
