Given :
PROFESSOR(NAME,OFFICE,DEPARTMENT,AGE)
COURSE(CNO,TITLE,DEPARTMENT)
ENROLL(CNO,SEMESTER,INSTRUCTOR_NAME,ENROLLMENT)
Find names of professors who taught all the courses in their department. Your solution must not use the division operator.
Is this question solvable using relational algebra?
I feel that this is not possible, even with the use of division operator. Unless we do it repeatedly for each professor name or for a particular department.
Any great ideas?
Is this question solvable using relational algebra?
Yes, it is. "All" is a clue to consider relational division.
But relational division is not a primitive operator. So you can "use" it without using it by using the operators by which it can be defined. There are many sources for learning about "all" and division queries.
(The conditions for tuples to be returned for "all the" and "at least the" queries, including those for which division is and is not appropriate, involve using the formal "forall X" and "not exists X". And "and not" leads to algebraic "minus" while "exists X" leads to algebraic "project all attributes but X". And often is is simpler to reason about such conditions using relational subset-of: A first relation is a subset of a second when the tuple membership condition for the first implies the tuple membership condition for the second. And "P implies Q" means "not (P and not Q)". In which "and not" turns up again.)
Related
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.
I have to write a program that tests whether two algebraic expressions are equivalent. It should follow MDAS precedence and parenthesis grouping. To solve the problem about precedence, I'm thinking I should implement a Infix to Postfix Notation converter for these expressions. But by doing this, I could not conclude their equivalence.
The program should look like this:
User Input: a*(a+b) = a*a + a*b
Output : Equivalent
For this problem I'm not allowed to use Computer Algebraic Systems or any external libraries. Please don't post the actual code if you have one, I just need an idea to work this problem out.
If you are not allowed to evaluate the expressions, you will have to parse them out into expression trees.
After that, I would get rid of all parenthesis by multiplying/dividing all members so a(b - c) becomes a*b - a*c.
Then convert all expressions back to strings, making sure you have all members alphabetically sorted (a*b, not b*a) ,remove all spaces and compare strings.
That's an idea:
You need to implement building expression tree first because it's a very natural representation of expression.
Then maybe you'll need to simplify it by open brackets and etc. using associative or distributive algebraic properties.
Then you'll have to compare trees. It's not obvious because you need to take care of all branch permutations in commutative operations and etc. E.g. you can sort them (I mean branches) and then compare for equality. Also you need to keep in mind possible renaming of parameters, i.e. a + b need to be equal x + y.
There are a lot of LINQ-based implementations of the Composite Specification Pattern. I have not seen one that used Subsumption.
Are there any such examples that have been documented (blogs, etc.) or published as open source? I have an idea and proof of concept for how this could work by having an ExpressionVisitor translate every specification into a canonical logical form (CNF/DNF), but I am concerned that this is overly complicated. Is there a better way?
I am concerned that this is overly complicated. Is there a better way?
The short answer is "No, there isn't" 1
The long answer: The "overly complicated" captures the essence of the problem: it is NP-hard. Here is a short informal proof relying upon the fact that the satisfiability problem is NP-complete:
Suppose that you have two Boolean formulas, A and B
You need to test if A implies B, or equivalently ¬A | B for all assignments of variables upon which A and B depend. In other words, you need a proof that F = ¬A | B is a tautology.
Suppose that the tautology test can be performed in polynomial time
Consider ¬F, the inverse of F. F is satisfiable if and only if ¬F is not a tautology
Use the hypothetical polynomial algorithm to test ¬F for being a tautology
The answer to "is F satisfiable" is the inverse of the answer to "is ¬F a tautology"
Therefore, an existence of a polynomial tautology checker would imply that the satisfiability problem is in P, and that P=NP.
Of course the fact that the problem is NP-hard does not mean that there would be no solutions for practical cases: in fact, your approach with the conversion to a canonical form may produce OK results in many real-world situations. However, an absence of a known "good" algorithm often discourages active development of practical solutions2.
1 With the obligatory "unless P=NP" disclaimer.
2 Unless a "reasonably good" solution would do, which may very well be the case for your problem, if you allow for "false negatives".
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.