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I'm reading about an algorithm (it's a path-finding algorithm based on A*), and it contains a mathematical symbol I'm unfamiliar with: ∀
Here is the context:
v(s) ≥ g(s) = mins'∈pred(s)(v(s') + c(s', s)) ∀s ≠ sstart
Can someone explain the meaning of ∀?
That's the "forall" (for all) symbol, as seen in Wikipedia's table of mathematical symbols or the Unicode forall character (\u2200, ∀).
The upside-down A symbol is the universal quantifier from predicate logic. (Also see the more complete discussion of the first-order predicate calculus.) As others noted, it means that the stated assertions holds "for all instances" of the given variable (here, s). You'll soon run into its sibling, the backwards capital E, which is the existential quantifier, meaning "there exists at least one" of the given variable conforming to the related assertion.
If you're interested in logic, you might enjoy the book Logic and Databases: The Roots of Relational Theory by C.J. Date. There are several chapters covering these quantifiers and their logical implications. You don't have to be working with databases to benefit from this book's coverage of logic.
In math, ∀ means FOR ALL.
Unicode character (\u2200, ∀).
Can be read, "For all s such that s does not equal s[start]"
yes, these are the well-known quantifiers used in math. Another example is ∃ which reads as "exists".
http://en.wikipedia.org/wiki/Quantification
Related
Consider the language
Consider the language
Aabb = {< M > | M is a TM, and M accepts abb}
a) What is the computational problem that is represented by Aabb?
b) Show that Aabb is undecidable.
I tried proving it but didn't know what to do.
You can use Rice's theorem directly and correctly prove the claim by noting that some TMs accept aab, some don't, and acceptance of abb is a semantic property of languages (it has to do only with the strings accepted, not the manner of accepting them). Rice guarantees this language is undecidable.
If you want another kind of proof, consider the following. There's nothing special about the string abb. If this problem is decidable, we'd expect the problem to be decidable for any arbitrary string. If it were decidable for any arbitrary string, we could use dovetailing to decide whether the language of the TM were empty. If we could decide whether the language of a TM were empty, we could take any TM, change all instances of halt-reject to halt-accept, and then decide whether the TM halts on at least one input. Etc. Etc. Basically, you can construct a chain of implications as long as you want but you quickly find known undecidable problems you can reduce to.
What is the exact difference between Well-formed formula and a proposition in propositional logic?
There's really not much given about Wff in my book.
My book says: "Propositions are also called sentences or statements. Another term formulae or well-formed formulae also refer to the same. That is, we may also call Well formed formula to refer to a proposition". Does that mean they both are the exact same thing?
Proposition: A statement which is true or false, easy for people to read but hard to manipulate using logical equivalences
WFF: An accurate logical statement which is true or false, there should be an official rigorus definition in your textbook. There are 4 rules they must follow. Harder for humans to read but much more precise and easier to manipulate
Example:
Proposition : All men are mortal
WFF: Let P be the set of people, M(x) denote x is a man and S(x)
denote x is mortal Then for all x in P M(x) -> S(x)
It is most likely that there is a typo in the book. In the quote Propositions are also called sentences or statements. Another term formulae or well-formed formulae also refer to the same. That is, we may also call Well formed formula to refer to a preposition, the word "preposition" should be "proposition".
Proposition :- A statement which is either true or false,but not both.
Propositional Form (necessary to understand Well Formed Formula) :- An assertion which contains at least one propositional variable.
Well Formed Formula :-A propositional form satisfying the following rules and any Wff(Well Formed Formula) can be derived using these rules:-
If P is a propositional variable then it is a wff.
If P is a propositional variable,then ~P is a wff.
If P and Q are two wffs then,(A and B),(A or B),(A implies B),(A is equivalent to B) are all wffs.
If I have a subset of logic programming which contains only one function symbol, am I able to do everything?
I think that I cannot but I am not sure at all.
A programming language can do anything user wants if it is a Turing-complete language. I was taught that this means it has to be able to execute if..then..else commands, recursion and that natural numbers should be defined.
Any help and opinions would be appreciated!
In classical predicate logic, there is a distinction between the formula level and the term level. Since an n-ary function can be represented as an (n+1)-ary predicate, restricting only the number of function symbols does not lessen the expressivity.
In prolog, there is no difference between the formula and the term level. You might pick an n-ary symbol p and try to encode turing machines or an equivalent notion(e.g. recursive functions) via nestings of p.
From my intution I would assume this is not possible: you can basically describe n-ary trees with variables as leaves, but then you can always unify these trees. This means that every rule head will match during recursive derivations and therefore you are unable to express any case distinction. Still, this is just an informal argument, not a proof.
P.S. you might also be interested in monadic logic, where only unary predicates are allowed. This fragment of first-order logic is decidable.
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I have to write a rule square(S) in Prolog that tests if a number S is the square of an integer returning false (ex. square(3)) or true (ex. square(4)).
I used already a rule that generates all integers between 0 and M:
isInteger(X,M) :- between(0,M,X).
Using this generator I have to write the rule square(S). How can I do it?
Thanks
This probably will not work as a solution for your homework, but here is one of many ways to do it using constraint logic programming in ECLiPSe CLP Prolog:
:- lib(gfd).
square(S) :-
sqr(_) #= S.
It means: S is a square if it's an integer and some other value (we don't care what value, so we use "throw-out" variable _) squared equals S.
All modern Prolog systems supports constraint logic programming, and the code will be similar to above.
To solve it your way, you just need to check if S is the product of your generated integer multiplied by itself. So you could do it like this:
isInteger(X,M) :- between(0,M,X).
square(N) :-
isInteger(X, N),
N is X * X.
I came up with another possible solution, using the sqrt arithmetical function from SWI-Prolog but I think there must be a more elegant one.
I initially expected it would be as simple as X is sqrt(4), integer(X). However, this doesn't work (at least not in SWI-Prolog 7.1.4), because X is unified with the float 2.0 and integer(2.0) is false (since integer is checking the data type, not the value of the number). But this works:
square_of_integer(N) :-
Int is rationalize(sqrt(N)),
integer(Int).
It depends on first giving a representation of N as a rational (which, in SWI-Prolog, 'are represented by the compound term rdiv(N,M)'). 2 is rationalize(2.0), i.e., rationalize evaluates to an integer for round numbers.
I was wondering what sort of sentences can't you express in Prolog? I've been researching into logic programming in general and have learned that first-order logic is more expressive compared to definite clause logic (Horn clause) that Prolog is based on. It's a tough subject for me to get my head around.
So, for instance, can the following sentence be expressed:
For all cars, there does not exist at least 1 car without an engine
If so, are there any other sentences that CAN'T be expressed? If not, why?
You can express your sentence straightforward with Prolog using negation (\+).
E.g.:
car(bmw).
car(honda).
...
car(toyota).
engine(bmw, dohv).
engine(toyota, wenkel).
no_car_without_engine:-
\+(
car(Car),
\+(engine(Car, _))
).
Procedure no_car_without_engine/0 will succeed if every car has an engine, and fail otherwise.
The most problematic definitions in Prolog, are those which are left-recursive.
Definitions like
g(X) :- g(A), r(A,X).
are most likely to fail, due to Prolog's search algorithm, which is plain depth-first-search
and will run to infinity and beyond.
The general problem with Horn Clauses however is, that they're defined to have at most one positive element. That said, one can find a clause which is limited to those conditions,
for example:
A ∨ B
As a consequence, facts like ∀ X: cat(X) ∨ dog(X) can't be expressed directly.
There are ways to work around those and there are ways to allow such statements (see below).
Reading material:
These slides (p. 3) give an
example of which sentence you can't build using Prolog.
This work (p. 10) also explains Horn Clauses and their implications and introduces a method to allow 'invalid' Horn Clauses.
Prolog is a programming language, not a natural language interface.
The sentence you show is expressed in such a convoluted way that I had hard time attempting to understand it. Effectively, I must thanks gusbro that took the pain to express it in understandable way. But he entirely glossed over the knowledge representation problems that any programming language pose when applied to natural language, or even simply negation in first order logic. These problems are so urgent that the language selected is often perceived as 'unimportant'.
Relating to programming, Prolog lacks the ability to access in O(1) (constant time) any linear data structure (i.e. arrays). Then a QuickSort, for instance, that requires access to array elements in O(1), can't be implemented in efficient way.
But it's nevertheless a Turing complete language, for what is worth. Then there are no statements that can't be expressed in Prolog.
So you are looking for sentences that can't be expressed in clausal logic that can be expressed in first order logic.
Strictly speaking, there are many, simply because clausal logic is a restriction of FOL. So that's true by definition.
What you can do though is you can rewrite any set of FOL sentences into a logic program that is not equivalent but with good properties. So for example if you want to know if p is a consequence of your theory, you can use equivalently the transformed logic program.
A few notes on the other answers:
Negation in Prolog (\+) is negation as failure and not first order logic negation
Prolog is a programming language, as correctly pointed out, we should be talking about clausal logic instead.
Left recursion is not a problem. You can easily use a different selection rule, or some other inference mechanism.