Theory of Computation | Cornell Engineering

 

theory of computation solved problems

INTRODUCTION TO THE THEORY OF COMPUTATION, SECOND EDITION MICHAEL SIPSER Massachusetts Institute of Technology THOMSON COURSE TECHNOLOGY Australia * Canada * Mexico * Singapore * Spain * United Kingdom * United States. Computational complexity theory focuses on classifying computational problems according to their inherent difficulty, and relating these classes to each other. A computational problem is a task solved by a computer. A computation problem is solvable by mechanical application of mathematical steps, such as . Theory of Computation Guided Textbook Solutions from Chegg. Chegg's step-by-step theory of computation guided textbook solutions will help you learn and understand how to solve theory of computation textbook problems and be better prepared for class.


Theory of computation - Wikipedia


In theoretical computer science and mathematicsthe theory of computation is the branch that deals with how efficiently problems can be solved on a model of computationusing an algorithm.

The field is divided into three major branches: automata theory and languages, computability theoryand computational complexity theorywhich are linked by the question: "What are the fundamental capabilities and limitations of computers? In order to perform a rigorous study of computation, theory of computation solved problems, computer scientists work with a mathematical abstraction of computers called a model of computation.

There are several models in use, but the most commonly examined is the Turing machine. So in principle, any problem that can be solved decided theory of computation solved problems a Turing machine can be solved by a computer that has a finite amount of memory. The theory theory of computation solved problems computation can be considered the creation of models of all kinds in the field of computer science. Therefore, mathematics and logic are used, theory of computation solved problems.

In the last century it became an independent academic discipline and was separated from mathematics. Automata theory is the study of abstract machines or more appropriately, abstract 'mathematical' machines or systems and the computational problems that can be solved using these machines. These abstract machines are called automata. Automata theory is also closely related to formal language theory, [5] as the automata are often classified by the class of formal languages they are able to recognize.

An automaton can be a finite representation of a formal language that may be an infinite set. Automata are used as theoretical models for computing machines, and are used for proofs about computability.

Language theory is a branch of mathematics concerned with describing languages as a set of operations over an alphabet. It is closely linked with automata theory, as automata are used to generate and recognize formal languages. There are several classes of formal languages, each allowing more complex language theory of computation solved problems than the one before it, i. Chomsky hierarchy[6] and each corresponding to a class of automata which recognizes it.

Because automata are used as models for computation, formal languages are the preferred mode of specification for any problem that must be computed. Computability theory deals primarily with the question of the extent to which a problem is solvable on a computer. The statement that the halting problem cannot be solved by a Turing machine [7] is one of the most important results in computability theory, as it is an example of a concrete problem that is both easy to formulate and impossible to solve using a Turing machine.

Much of computability theory builds on the halting problem result. Another important step in computability theory was Rice's theoremwhich states that for all non-trivial properties of partial functions, it is undecidable whether a Turing machine computes a partial function with that property.

Computability theory is closely related to the branch of mathematical logic called recursion theorywhich removes the restriction of studying only models of computation which are reducible to the Turing model. Complexity theory considers not only whether a problem can be solved at all on a computer, but also how efficiently the problem can be solved.

Two major aspects are considered: time complexity and space complexity, which are respectively how many steps does it take to perform a computation, and how much memory is required to perform that computation.

In order to analyze how much time and space a given algorithm requires, computer scientists express the time or space required to solve the problem as a function of the size of the input problem. For example, finding a particular number in a long list of numbers becomes harder as the list of numbers grows larger. If we say there are n numbers in the list, then if the list is not sorted or indexed in any way we may have to look at every number in order to find the number we're seeking.

We thus say that in order to solve this problem, the computer needs to perform a number of steps that grows linearly in the size of the problem. To simplify this problem, computer scientists have adopted Big O notationwhich allows functions to be compared in a way that ensures that particular aspects of a machine's construction do not need to be considered, but rather only the asymptotic behavior as problems become large. Perhaps the most important open problem in all of computer science is the question of whether a certain broad class of problems denoted NP can be solved efficiently.

Aside from a Turing machineother equivalent See: Church—Turing thesis models of computation are in use. In addition to the general computational models, some simpler computational models are useful for special, restricted applications. Regular expressionsfor example, specify string patterns in many contexts, from office productivity software to programming languages. Another formalism mathematically equivalent to regular expressions, Finite automata are used in circuit design and in some kinds of problem-solving.

Context-free grammars specify programming language syntax. Non-deterministic pushdown automata are another formalism equivalent to context-free grammars. Primitive recursive functions are a defined subclass of the recursive functions, theory of computation solved problems. Different models of computation have the ability to do different tasks.

One way to measure the power of a computational model is to study the class of formal languages that the model can generate; in such a way to the Chomsky hierarchy of languages is obtained.

From Wikipedia, the free encyclopedia. Not to be confused with computational theory of mind. For the journal, see Theory of Computing. Main article: Automata theory, theory of computation solved problems. Main article: Formal language. Main article: Computability theory, theory of computation solved problems. Main article: Computational complexity theory.

Main article: Model of computation. Introduction to the Theory of Computation 3rd. Cengage Learning.

Princeton University Press. June Mathematical Logic. Ullman Introduction to Automata Theory, theory of computation solved problems, Languages, and Computation. Reading, MA: Addison-Wesley. Proceedings of the London Mathematical Society. Retrieved 6 January Transactions of the American Mathematical Society. American Mathematical Society. The undecidable: Basic papers on undecidable propositions, unsolvable problems and computable functions Dover Ed. Dover Publications.

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Computational complexity theory - Wikipedia

 

theory of computation solved problems

 

Computer scientists are still investigating whether some computational complexity classes of decision problems may in fact be equal. A famous open area in computer science is the "Does P=NP?" question: are all YES/NO problems that can be verified quickly (NP) actually problems that can be directly solved Author: Prof. Michael Sipser. Aug 24,  · Theory of Computation is one of the most fundamental as well as abstract courses of Computer Science. It is a branch in theoretical Computer Science that deals with whether problems can be solved. INTRODUCTION TO THE THEORY OF COMPUTATION, SECOND EDITION MICHAEL SIPSER Massachusetts Institute of Technology THOMSON COURSE TECHNOLOGY Australia * Canada * Mexico * Singapore * Spain * United Kingdom * United States.