18-08-2012, 03:38 PM
Artificial Intelligence
Introduction-to-Artificial-Intelligence.pdf (Size: 5.6 MB / Downloads: 209)
Introduction
What Is Artificial Intelligence?
The term artificial intelligence stirs emotions. For one thing there is our fascination
with intelligence, which seemingly imparts to us humans a special place among
life forms. Questions arise such as “What is intelligence?”, “How can one measure
intelligence?” or “How does the brain work?”. All these questions are meaningful
when trying to understand artificial intelligence. However, the central question for
the engineer, especially for the computer scientist, is the question of the intelligent
machine that behaves like a person, showing intelligent behavior.
The attribute artificial might awaken much different associations. It brings up
fears of intelligent cyborgs. It recalls images from science fiction novels. It raises
the question of whether our highest good, the soul, is something we should try to
understand, model, or even reconstruct.
Brain Science and Problem Solving
Through research of intelligent systems we can try to understand how the human
brain works and then model or simulate it on the computer. Many ideas and principles
in the field of neural networks (see Chap. 9) stem from brain science with the
related field of neuroscience.
A very different approach results from taking a goal-oriented line of action, starting
from a problem and trying to find the most optimal solution. How humans solve
the problem is treated as unimportant here. The method, in this approach, is secondary.
First and foremost is the optimal intelligent solution to the problem. Rather
than employing a fixed method (such as, for example, predicate logic) AI has as its
constant goal the creation of intelligent agents for as many different tasks as possible.
Because the tasks may be very different, it is unsurprising that the methods
currently employed in AI are often also quite different. Similar to medicine, which
encompasses many different, often life-saving diagnostic and therapy procedures,
AI also offers a broad palette of effective solutions for widely varying applications.
For mental inspiration, consider Fig. 1.2 on page 4. Just as in medicine, there is no
universal method for all application areas of AI, rather a great number of possible
solutions for the great number of various everyday problems, big and small.
The Turing Test and Chatterbots
Alan Turing made a name for himself as an early pioneer of AI with his definition
of an intelligent machine, in which the machine in question must pass the following
test. The test person Alice sits in a locked room with two computer terminals. One
terminal is connected to a machine, the other with a non-malicious person Bob.
Alice can type questions into both terminals. She is given the task of deciding, after
five minutes, which terminal belongs to the machine. The machine passes the test if
it can trick Alice at least 30% of the time [Tur50].
Logic Solves (Almost) All Problems
AI as a practical science of thought mechanization could of course only begin once
there were programmable computers. This was the case in the 1950s. Newell and
Simon introduced Logic Theorist, the first automatic theorem prover, and thus also
showed that with computers, which actually only work with numbers, one can also
process symbols. At the same time McCarthy introduced, with the language LISP,
a programming language specially created for the processing of symbolic structures.
Both of these systems were introduced in 1956 at the historic Dartmouth Conference,
which is considered the birthday of AI.
Introduction-to-Artificial-Intelligence.pdf (Size: 5.6 MB / Downloads: 209)
Introduction
What Is Artificial Intelligence?
The term artificial intelligence stirs emotions. For one thing there is our fascination
with intelligence, which seemingly imparts to us humans a special place among
life forms. Questions arise such as “What is intelligence?”, “How can one measure
intelligence?” or “How does the brain work?”. All these questions are meaningful
when trying to understand artificial intelligence. However, the central question for
the engineer, especially for the computer scientist, is the question of the intelligent
machine that behaves like a person, showing intelligent behavior.
The attribute artificial might awaken much different associations. It brings up
fears of intelligent cyborgs. It recalls images from science fiction novels. It raises
the question of whether our highest good, the soul, is something we should try to
understand, model, or even reconstruct.
Brain Science and Problem Solving
Through research of intelligent systems we can try to understand how the human
brain works and then model or simulate it on the computer. Many ideas and principles
in the field of neural networks (see Chap. 9) stem from brain science with the
related field of neuroscience.
A very different approach results from taking a goal-oriented line of action, starting
from a problem and trying to find the most optimal solution. How humans solve
the problem is treated as unimportant here. The method, in this approach, is secondary.
First and foremost is the optimal intelligent solution to the problem. Rather
than employing a fixed method (such as, for example, predicate logic) AI has as its
constant goal the creation of intelligent agents for as many different tasks as possible.
Because the tasks may be very different, it is unsurprising that the methods
currently employed in AI are often also quite different. Similar to medicine, which
encompasses many different, often life-saving diagnostic and therapy procedures,
AI also offers a broad palette of effective solutions for widely varying applications.
For mental inspiration, consider Fig. 1.2 on page 4. Just as in medicine, there is no
universal method for all application areas of AI, rather a great number of possible
solutions for the great number of various everyday problems, big and small.
The Turing Test and Chatterbots
Alan Turing made a name for himself as an early pioneer of AI with his definition
of an intelligent machine, in which the machine in question must pass the following
test. The test person Alice sits in a locked room with two computer terminals. One
terminal is connected to a machine, the other with a non-malicious person Bob.
Alice can type questions into both terminals. She is given the task of deciding, after
five minutes, which terminal belongs to the machine. The machine passes the test if
it can trick Alice at least 30% of the time [Tur50].
Logic Solves (Almost) All Problems
AI as a practical science of thought mechanization could of course only begin once
there were programmable computers. This was the case in the 1950s. Newell and
Simon introduced Logic Theorist, the first automatic theorem prover, and thus also
showed that with computers, which actually only work with numbers, one can also
process symbols. At the same time McCarthy introduced, with the language LISP,
a programming language specially created for the processing of symbolic structures.
Both of these systems were introduced in 1956 at the historic Dartmouth Conference,
which is considered the birthday of AI.