When you are proving a language is decidable, what are you effectively doing?
If you asking HOW is it done, I'm unsure, but I can check.
Basically, decidable is the language for which one can construct an algorithm (i.e. Turing machine) that will halt for ANY finite input (with accepting or rejecting the input).
Undecidable is the language which is not decidable.
http://en.wikipedia.org/wiki/Recursive_language ... but more on the subject can easily be found. On this link there is only a quick mention of the term.
p.s. So, when constructing above mentioned algorithm, you are basically proving that language is decidable.
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Can an NFA ever accept a string which is not in the language?
I know that for an NFA to accept a string there has to be atleast one way by which it gets accepted and we can safely say that the NFA accepts it.
But in case of Rejection ...can at times it may happen that if a string which doesn't belong to the language getting accepted by NFA?
The definition of the language accepted by an NFA says that it is the set of all strings that are accepted by the NFA. So clearly, every string that is accepted belongs to the language, and thus the answer to your question is: No.
Rejection means: all possible computations for the given string either end in a non-accepting state or do not even read the entire string (if the automaton is not complete). Both of these possibilities exclude acceptance.
For non-deterministic Turing Machines there exist notions of acceptance like: "more than half of the computations accept," or "an odd number of computations accept" (Parity) etc. There you can have accepting computations despite global rejection. But these notions are not widely used and I have never seen them applied to finite automata.
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I'm trying to understand context-sensitive grammars, and I understand why languages like
{ww | w is a string}
{an bn cn | a,b,c are symbols}
are not context free, but what I'd like to know if a language similar to the untyped lambda calculus is context sensitive. I'd like to see an example of a simple, but non-toy (I consider the above toy examples), example of a context-sensitive grammar that can, for some production rule, e.g., tell whether or not some string of symbols is in scope currently (e.g. when producing the body of a function). Are context sensitive grammars powerful enough to make undefined/undeclared/unbound variables a syntactic (rather than semantic) error?
Yes, context-sensitive grammars (CSG) are powerful enough to make undefined/undeclared/unbound variables check, but unfortunately we don't know any efficient algorithm to parse strings of CSG.
A real example of a context-sensitive language is the C programming language. A feature like declare variables first and then use them later make C-language a context-sensitive language (CSL). (I don't know about untyped lambda calculus).
And because we don't know any linear parsing algorithm for CSL (or CSG). That is the reason in compiler design, we use CFG (and its parsing algoritm only) for syntax checking since we know efficient algorithms to parse CFG (if it's in restricted form). Compilers first parse a context free feature and then later handle context-sensitive features in a problematically way (for example, checks any used variable in the symbol table if it's defined. Otherwise, it generates an error).
Also context-sensitive grammar is used in natural-language processing (NLP). And most natural languages are examples of context-sensitive languages. (I am not sure for the Sanskrit language).
I will try to explain it with a silly but simple example (it's just an idea, you can refine it):
NOUN --> { BlueBomber, Grijesh, I, We}
TENSE --> { am, was, is, were}
VERB --> { going, eating, working}
SENTENCE --> <NOUN> <TENSE> <VERB>
Now, using this grammar, we can generate some correct statements, but some are wrong too. For example,
SENTENCE --> <NOUN> <TENSE> <VERB>
Grijesh is working [Correct statement]
But
Grijesh am working [wrong statement]
Reason: the value of <TENSE> depends on value <NOUN> (for example, I <TENSE> --> I am) and hence the grammar doesn't generate correct statements in the English language.
Actually we can't write a context-free grammar for complete English!
You might have noticed, any natural language translator or grammar checker doesn't works correctly (try with long statements). Because this problem comes under the context-sensitive parsing algorithm.
REFERENCE: You can watch Dr. Arun Kumar's lectures.
In some lecture he explains exactly what you are interested in.
I'm looking for the mathematical theory which deals with describing formal languages (set of strings) in general and not just grammar hierarchies.
Grammars give you the algorithm that lists all possible strings in the language. You could specify the algorithm any other way, but grammars are a concise and well-accepted format to do so.
Another way is to list every string that belongs to the language -- this will only work if the set of strings in the language is small (and definitely not when the set is infinite).
Regular expressions are a formalism for describing a set of languages, for instance. Although there are algorithms for transforming regular grammars and expressions in both ways, they are still two different theories. Also, automata (as a plural of automaton) can help you describe languages, not just DFA and NFA which describe the same set as regular languages, but 2DFA, stack automata. For example, a two-stacks automata is as powerful as a Turing machine. Finally, Turing machines itself are a formalism for languages. For any Turing machine, the set of all string on which the given Turing machine stops on a finite number of steps is a formally defined language.
I'm trying to find a plain (i.e. non-formal) explanation of the 4 levels of formal grammars (unrestricted, context-sensitive, context-free, regular) as set out by Chomsky.
It's been an age since I studied formal grammars, and the various definitions are now confusing for me to visualize. To be clear, I'm not looking for the formal definitions you'll find everywhere (e.g. here and here -- I can google as well as anyone else), or really even formal definitions of any sort. Instead, what I was hoping to find was clean and simple explanations that don't sacrifice clarity for the sake of completeness.
Maybe you get a better understanding if you remember the automata generating these languages.
Regular languages are generated by regular automata. They have only have a finit knowledge of the past (their compute memory has limits) so everytime you have a language with suffixes depending on prefixes (palindrome language) this can not be done with regular languages.
Context-free languages are generated by nondeterministic pushdown automata. They have a kind of knowledge of the past (the stack, which is not limited in contrast to regular automata) but a stack can only be viewed from top so you don't have complete knowledge of the past.
Context-sensitive languages are generated by linear-bound non-deterministic turing machines. They know the past and can deal with different contexts because they are non-deterministic and can access all the past at every time.
Unrestricted languages are generated by Turing machines. According to the Church-Turing-Thesis turing machines are able to calculate everything you can imagine (which means everything decidable).
As for regular languages, there are many equivalent characterizations. They give many different ways of looking at regular languages. It is hard to give a "plain English" definition, and if you find it hard to understand any of the characterizations of regular languages, it is unlikely that a "plain English" explanation will help. One thing to note from the definitions and various closure properties is that regular languages embody the notion of "finiteness" somehow. But this is again hard to appreciate without better familiarity with regular languages.
Do you find the notion of a finite automaton to be not simple and clean?
Let me mention some of the many equivalent characterizations (at least for other readers) :
Languages accepted by deterministic finite automata
Languages accepted by nondeterministic finite automata
Languages accepted by alternating finite automata
Languages accepted by two-way deterministic finite automata
Languages generated by left-linear grammars
Languages generated by right-linear grammars
Languages generated by regular expressions.
A union of some equivalence classes of a right-congruence of finite index.
A union of some equivalence classes of a congruence of finite index.
The inverse image under a monoid homomorphism of a subset of a finite monoid.
Languages expressible in monadic second order logic over words.
Regular: These languages answer yes/no with finite automata
Context free: These languages when given input word ( using state machiene and stack ) we can always answer yes/no if it is member of the language
Context sensitive: As long as production in grammar never shrinks ( α -> β ) we can answer yes/no (using state machiene and chunk of memory that is linear in size with input)
Recursively ennumerable: It can answer yes but in case of no it will go into infinite loop
see this video for full explanation.
I just wanted to know if it is 100% possible, if my language is turing-complete, to write a program in it that prints itself out (of course not using a file reading function)
So if the language just has the really necessary things in order to make it turing complete (I would prove that by translating Brainf*ck code to it), like output, variables, conditions and gotos (hell yes, gotos), can I try writing a quine in it?
I'm also asking this because I'm not sure that a quine directly fits into Turing's law that the turing machine is capable of any computational task.
I just want to know so I don't try for years without knowing that it may be impossible.
Any programming language which is
Turing complete, and which is able to
output any string (by a computable
function of the string as program —
this is a technical condition that is
satisfied in every programming
language in existence) has a quine
program (and, in fact, infinitely many
quine programs, and many similar
curiosities) as follows by the
fixed-point theorem.
See here
I ran into this issue a couple of months ago.
While writing a quine doesn't necessarily prove that a language is Turing Complete, it is a strong suggestion ;) As far as Turing Completeness goes, if you can (like you said) provide a valid translation from your language to another Turing-Complete language, then your language is Turing Complete.
That being said, any language that is Turing Complete that can output a string should be able to generate a quine. Also, from Wikipedia:
A quine is a fixed point of an execution environment, when the execution environment is viewed as a function. Quines are possible in any programming language that has the ability to output any computable string, as a direct consequence of Kleene's recursion theorem. For amusement, programmers sometimes attempt to develop the shortest possible quine in any given programming language.
It is possible to have a programming language that cannot print all the symbols in its representation. For example, the I/O may be limited to 7-bit ASCII characters with language keywords in Arabic. That's the only exception I can think of.
Well, technically, not always. According to the proof on Wikipedia, the programming language has to be an admissible numbering. Practical and sane Turing-complate programming languages are all admissible numberings. And a Turing-complate programming language is an admissible numbering if it's possible to translate between that and another admissible numbering.
An example Turing-complete programming language that is not an admissible numbering:
The source code always contains one or two doublequoted escaped strings. If the input is empty, output the first string if there are two strings, or loop forever if there is one. Otherwise, evaluate the last string in Python, using the original input as input.
It's not an admissible numbering because, given a Python program, we have to know its behavior when the input is empty, to translate it into this language. But we may never know if it is an infinite loop, as we cannot solve the halting problem. We know a translation always exists, though.
It's impossible to write quines in this language.