Using computers as an example, just whack it a few times until lights flash. You might discover a new 'undecidable' problem.
Stephen reduction is a method used in computability theory to show that a problem is undecidable by reducing a known undecidable problem to the problem in question. This technique was developed by J. Barry Stephen in the 1960s as a way to prove the undecidability of various problems in mathematics and computer science. By demonstrating that the known undecidable problem can be transformed into the new problem, it follows that the new problem is also undecidable.
Yes, the halting problem is undecidable, meaning that there is no algorithm that can determine whether a given program will halt or run indefinitely.
if it halts
Yes, the problem of determining whether a given context-free grammar (CFG) is undecidable.
Yes, the halting problem is not NP-hard, it is undecidable.
An example of an undecidable language is the Halting Problem, which involves determining whether a given program will eventually halt or run forever. This problem cannot be solved by any algorithm.
The following are undecidable cfl problems: If A is a cfl - Does A = Sigma star? If A & B cfls - is A a contained within B?
No, the halting problem is undecidable, meaning there is no algorithm that can determine whether a given program will halt or run forever.
An undecidable problem is a question that cannot be answered by a computer program. This impacts computer science because it shows the limitations of what computers can do, and raises important questions about the nature of computation and the boundaries of what is possible with technology.
Undecidable languages are languages for which there is no algorithm that can determine whether a given input string is in the language or not. Examples of undecidable languages include the Halting Problem and the Post Correspondence Problem. Decidable languages, on the other hand, are languages for which there exists an algorithm that can determine whether a given input string is in the language or not. Examples of decidable languages include regular languages and context-free languages. The key difference between undecidable and decidable languages is that decidable languages have algorithms that can always provide a definite answer, while undecidable languages do not have such algorithms.
Yes, proving decidability is a necessary step in determining the computability of a problem. Decidability refers to the ability to determine whether a problem has a definite answer or not. If a problem is undecidable, it cannot be computed by a computer. Therefore, proving decidability is crucial in understanding the limits of computability for a given problem.
People did not discover about it, scientists did. They did it in 1985.