Automata?
It is plural of automaton simply define as "something that works automatically".
Example Of Automaton:
• Computer
Automata is concerned with mathematical models which are foundations of computing. These theoretical concepts will not vary with the next new model of computers.
A firm knowledge of the theoretical basis for computation will give you a stable platform from which to observes and understand the dazzling progress being made in the production of new computers and software..
History Of Automata:
In the 1930’s, Alan Turing (1912 – 1952), an English mathematician, studied an abstracts machine called Turing machine even before computers existed!
• He is regarded as pioneer of automata theory
Turing Machine:
The goal
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In the 1940’s and 1950’s, machines currently called “Finite Automata” were studied by a number of researchers:
• Initially proposed to model the brain function.
• Later used for variety of others purposes. 2. In late 1950’s, the Linguist N. Chomsky introduced formal grammar.
• Has close relationship to abstracts automata.
• Also important in development of software components and compiler. 3. In 1969, S. Cook extended the theory of Turing:
• what could be solved and what couldn’t.
Computability:
• S. Cook separated the solvable problems from those that can in principles be solved by a computer, but in practice, take so much time that computers are useless for all but very small instances of these problems.
• Latter class of problems are called “intractable or NP-hard.
• Complexity of Problems
Description Of Automata Theory:
Automata Theory is an interesting and in theoretical branch of computer science .Automata is the study of "abstract" computing devices machines and their algorithms.
• Also called theory of computation .irrelevant complications are dropped in order to focus on important concept.
• Automata theory help ensure the safety critical systems are correct.
• It helps create abstract models for
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•Length of string w is denoted as |w|
•Let w = 10011
–|w| = 5
–|ϵ| = ?
•0
–x = 01 ϵ 0 ϵ 1 ϵ 00 ϵ |x| = ?
•6
•xy = concatenation of two strings x and y
•ϵ being the identity for concatenation
•x is said to be prefix of y if xz = y for some z.
•z is said to be suffix of x if xz = y.
Language And Grammar:
•A language is a set of words.
•E.g.
–Given Σ = {0,1}, we may define a language L = {00, 01,10, - - -}.
•A grammar is a finite list of rules defining a language.
–Enumerates words of a language - nothing more, nothing less.
Powers Of An Alphabet:
•Σk = the set of all strings of length k
•E.g. Σ = {a, b, c}
–Σ1 = ? •{a, b, c}
–Σ2 = ?
•{aa, ab, ac, ba, bb, bc, ca, cb, cc}
–Σ0 = ? •{ϵ}
•The set of all strings over an alphabet Σ is denoted by Σ*
–Σ* = Σ0 U Σ1 U Σ2 U …
•E.g. Σ = {0, 1}, then Σ* = ?
–Σ* = {ϵ, 0, 1, 00, 01, 10, 11, 000, . . . } •The set of all non-empty strings over an alphabet Σ is denoted by Σ+
–Σ+ = Σ1 U Σ2 U … or equivalently,
–Σ* = {ϵ} U Σ+
Language:
•L is said to be a language over alphabet Σ only if L Σ*
•Example
–Let L (defined over Σ = {0, 1}), be the language of all strings consisting of n 0’s followed by n
All languages could be successfully analyzed in terms of mathematical equations. In this sense, language is mathematics. This thesis enables us to explain why languages usually have different word orders, and why any language could be highly flexible.
Andy Clark strongly argues for the theory that computers have the potential for being intelligent beings in his work “Mindware: Meat Machines.” The support Clark uses to defend his claims states the similar comparison of humans and machines using an array of symbols to perform functions. The main argument of his work can be interpreted as follows:
In this paper I will evaluate and present A.M. Turing’s test for machine intelligence and describe how the test works. I will explain how the Turing test is a good way to answer if machines can think. I will also discuss Objection (4) the argument from Consciousness and Objection (6) Lady Lovelace’s Objection and how Turing responded to both of the objections. And lastly, I will give my opinion on about the Turing test and if the test is a good way to answer if a machine can think.
In the 1940s and 1950s scientists began to discuss the possibility of creating an artificial brain. Research sped up after neurologists discovered that the brain is an electrical network of neurons. Then, in 1950, Alan Turing published a paper in which he discussed the possibility of creating machines that think. Since "thinking" is difficult to define, he created the “Turing Test.” The test stated that a machine could “think” if it was able to carry on a teleprinter conversation that was indistinguishable from a human
I shall also expound Ayer's theory of knowledge, as related in his book. I will show this theory to contain logical errors, making his modified version of the principle flawed from a second angle.
In this essay, I describe in detail a hypothetical test contemporarily known as the Turing test along with it’s respective objective. In addition, I examine a distinguished objection to the test, and Turing’s consequential response to it.
The website for Princeton University’s Computer Science department offers a great analogy of the subject, “What energy is to physics, information is to computer science.”
Artificial intelligence folklore has been traced back to the times of Ancient Egypt. But the "birth of artificial intelligence" as some would call it, was in 1956 at the Dartmouth conference. The conference was based on two theories, the principle of feedback theory and the Logic Theorist. The principle of feedback theory was observed by Norbert Wiener. He theorized that all intelligent behavior was the result of a feedback mechanism. An example would be a temperature control system that simply checks the temperature of the room, compares the reading to the desired temperature, and adjusts the flow of heat to bring the room to the desired temperature. Then in 1955, Newell and Simon developed The Logic Theorist. The Logic Theorist was a program that represented every problem as a tree. The program would attempt to solve a problem by selecting the branch that would most likely result in the correct solution. Then in 1956, John McCarthy1 organized the Dartmouth Conference to draw interest and talent to the field of artificial intelligence.2
Years later in 1956 John Von Neumann would develop one of the most influential computers called the JOHNNIAC (John V. Neumann Integrator and Computer). The JOHNNIAC was an early effort at AI prog...
Although the majority of people cannot imagine life without computers, they owe their gratitude toward an algorithm machine developed seventy to eighty years ago. Although the enormous size and primitive form of the object might appear completely unrelated to modern technology, its importance cannot be over-stated. Not only did the Turing Machine help the Allies win World War II, but it also laid the foundation for all computers that are in use today. The machine also helped its creator, Alan Turing, to design more advanced devices that still cause discussion and controversy today. The Turing Machine serves as a testament to the ingenuity of its creator, the potential of technology, and the glory of innovation.
The legitimacy of apes’ understanding of human language is a much-deliberated topic. Though many apes have been trained to understand and use American Sign Language, the degree to which they exhibit comprehension of the properties of human language seems to vary. The apes Sherman and Austin, were able to use symbols to describe objects that were not immediately present and also to describe their intended actions, which is demonstrative of the displacement property. Sherman and Austin could also look at a certain set of printed lexigram symbols and denote whether each could be classified as either a ‘tool’ or a ‘food.’ Since they were never told beforehand which lexigram symbol corresponded to which classification, the apes were successfully demonstrating the arbitrariness property of language. Apes have even demonstrated making their own language rules, such as using...
The most common refutation to the notion of mental states in digital computers is that there are inherent limits of computation and that there are inabilities that exist in any algorithm to...
...ite number of thoughts, feelings, and more. The infiniteness distinguishes this language from a the finite nature of sound and gestures in that important way, so this type of spoken, written language would still be the first of its sort that is acquired.
For a regular language, for every i, x z should be in language L1 where i>=0
Technology continued to prosper in the computer world into the nineteenth century. A major figure during this time is Charles Babbage, designed the idea of the Difference Engine in the year 1820. It was a calculating machine designed to tabulate the results of mathematical functions (Evans, 38). Babbage, however, never completed this invention because he came up with a newer creation in which he named the Analytical Engine. This computer was expected to solve “any mathematical problem” (Triumph, 2). It relied on the punch card input. The machine was never actually finished by Babbage, and today Herman Hollerith has been credited with the fabrication of the punch card tabulating machine.