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(a) Find the resolvant of \((p \vee q)\) and \((\neg p \vee r)\) on \(p\). (b) Find the resolvant of \((p \vee q \vee r \vee s)\) and \((\neg p \vee \neg q \vee t)\) on \(p\). (c) Find the resolvant of \((p \vee q)\) and \(\neg p\) on \(p\). (d) Find the resolvant of \((p)\) and \((\neg p)\) on \(p\). (e) Which resolvant above from parts (a) through (d) is a tautology? Which is tautologically false?

Short Answer

Expert verified
The resolvant from part (d) is tautologically false. No tautology exists among them.

Step by step solution

01

Understanding Resolution

Resolution is a rule in propositional logic for finding conclusions from two premises. If you have two clauses, one containing a literal and the other containing its negation, the resolution rule allows you to produce a new clause excluding the literal and its negation but including the rest of the literals from both clauses.
02

Resolving (p ∨ q) and (¬p ∨ r) on p

For the clauses \(p \vee q\) and \(eg p \vee r\), resolve on \(p\):- The literal \(p\) in the first clause is positive.- The literal \(eg p\) in the second clause is negative.- The resolvent of these is found by taking the remaining literals \(q\) and \(r\), resulting in the clause \(q \vee r\).
03

Resolving (p ∨ q ∨ r ∨ s) and (¬p ∨ ¬q ∨ t) on p

For the clauses \(p \vee q \vee r \vee s\) and \(eg p \vee eg q \vee t\), resolve on \(p\):- Remove \(p\) from the first clause and \(eg p\) from the second.- Merge the remaining literals: \(q \vee r \vee s \vee eg q \vee t\).- By simplifying, we observe that \(q\) and \(eg q\) cancel out to create a tautology, leaving us with \(r \vee s \vee t\).
04

Resolving (p ∨ q) and ¬p on p

For the clauses \(p \vee q\) and \(eg p\), resolve on \(p\):- Literal \(p\) is positive in the first clause, and \(eg p\) is negative in the second.- The resolvent is the remaining literal \(q\), as there are no additional literals in the second clause.
05

Resolving (p) and (¬p) on p

For the clauses \(p\) and \(eg p\), resolve on \(p\):- Literal \(p\) and \(eg p\) are direct opposites.- The resolution step results in an empty clause, indicating a contradiction, often called tautologically false.
06

Analyzing Results

Review each resolved clause to determine if it is a tautology or requires no further computation.- From part (a), \(q \vee r\) is not a tautology.- From part (b), no redundant literals appear, resulting in \(r \vee s \vee t\), not a tautology.- From part (c), the clause \(q\) is not a tautology.- From part (d), the resulting empty clause is tautologically false.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Tautology in Logic
In logic, a **tautology** refers to a formula or statement that is always true, regardless of the truth values of its components. This concept is essential because knowing whether an expression is tautological can simplify logical reasoning or proofs significantly.

The defining characteristic of a tautology is its unconditional truth. Consider the expression ``` (p ∨ ¬p) ``` For any value of the proposition **p**—whether true or false—this expression will invariably yield a truth value of true. This is because if **p** is true, then **p** within the disjunction ( ``` ∨ ``` ) will be true, thus validating the entire statement. If **p** is false, then ``` ¬p ``` , i.e., the negation, will be true, again confirming the truth of the complete expression.

Understanding tautologies is crucial when working with propositional logic, as they can help identify clauses that do not require further evaluation. In the exercise above, none of the results from the resolvants were tautologies, indicating that each required further consideration when analyzing logical outcomes.
Contradiction in Logic
A **contradiction** in logic is the opposite of a tautology. It is a statement or formula that is invariably false, regardless of the truth values of its constituent propositions. Understanding contradictions is key to identifying impossible scenarios in logical reasoning.

Consider the expression ``` (p ∧ ¬p) ``` . For any proposition **p**, it is impossible for both **p** and its negation ``` ¬p ``` to be true at the same time. Therefore, this conjunction ( ``` ∧ ``` ) will always be false, representing a tautologically false or logically impossible statement.

In the step-by-step solution provided above, the part (d) resulted in an empty clause after resolution, which is interpreted as a contradiction. This means that the simultaneous truth of **p** and ``` ¬p ``` is impossible, confirming that the resolved clause cannot be true under any circumstances.

Recognizing contradictions can be particularly useful in proofs, especially in indirect proofs or when confirming inconsistencies in logic-based problems.
Literal in Propositional Logic
In the realm of propositional logic, a **literal** is the most basic component of a clause or expression. It can be a straightforward proposition (like **p**) or the negation of a proposition (like ``` ¬p ``` ). Understanding literals is fundamental to dealing with propositional logic because they form the building blocks of more complex logical expressions.

When dealing with resolution in propositional logic, such as in the exercises provided, it is essential to accurately identify and handle literals. Each resolution step involves choosing a literal that appears in its original form in one clause and in its negated form in another. The theorem of resolution then allows you to eliminate these literals and combine the remaining ones to form a new clause.

For instance, when resolving clauses such as ``` (p ∨ q) ``` and ``` (¬p ∨ r) ``` , the literal **p** is handled by removing both **p** and ``` ¬p ``` to produce the resolvent ``` q ∨ r ``` . This simplification plays a critical role in logic-based problem-solving, allowing one to simplify complex expressions and draw conclusions efficiently.

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Most popular questions from this chapter

This problem concerns the following six sets: $$\begin{array}{c}A=\\{0,2,4,6\\} \quad B=(1,3,5) \quad C=\\{0,1,2,3,4,5,6,7\\} \\\D=\emptyset \quad E=\mathbb{N} \quad F=\\{10,2,4,6\\} \mid\end{array}$$ (a) What sets are subsets of \(A\) ? (b) What sets are subsets of \(B\) ? (c) What sets are subsets of \(C\) ? (d) What sets are subsets of \(D\) ? (c) What sets are subsets of \(E\) ? (f) What sets are subsets of \(F\) ?

The length of a clause is the number of literals in the clause. The length of a CNF formula is the sum of the length of its clauses. The number of excess literals in a CNF formula is the length of the formula minus the number of clauses in the formula. (a) Show that if an unsatisfiable set \(S\) of clauses contains only clauses of length 0 and 1 , it has a resolution refutation. (Hint: Prove the following: If \(S\) contains a clause of length 0 , it has [trivially] a resolution refutation. If, for some proposition letter \(p, S\) contains both \(p\) and \(\neg p,\) then \(S\) has a resolution refutation. Otherwise, \(S\) is satisfiable.) (b) Show that if a set \(\left\\{\lambda_{1} \vee \lambda_{2} \vee \ldots \vee \lambda_{k} \vee \lambda_{k+1}+\cup S(k \geq 1)\right.\) of clauses is un- satisfiable, so are \(\left\\{\lambda_{1} \vee \lambda_{2} \vee \lambda_{k}\right\\} \cup S\) and \(\left\\{\lambda_{k+1}\right\\} \cup S\). (Hint: For the first half, prove that if an interpretation \(I\) satisfies \(\left\\{\lambda_{1} \vee \lambda_{2} \vee \ldots \vee \lambda_{k}\right\\} \cup S,\) it also satisfies \(\left.\left\\{\lambda_{1} \vee \lambda_{2} \vee \cdots \vee \lambda_{k} \vee \lambda_{k+1}\right\\} \cup S_{.}\right)\) (c) Show that for \(k \geq 1,\) the number of excess literals in \(\left\\{\lambda_{1} \vee \lambda_{2} \vee \cdots \vee \lambda_{k}\right\\} \cup S\) and the number of excess literals in \(\left\\{\lambda_{k+1}\right\\} \cup S\) are both less than the number of excess literals in \(\left\\{\lambda_{1} \vee \lambda_{2} \vee \ldots \vee \lambda_{k} \vee \lambda_{k+1}\right\\} \cup S\). (d) A resolution derivation of a clause \(r_{k}\) from a set \(S\) of clauses is a sequence \(r_{0}, r_{1}, r_{2}, \ldots, r_{k}\) of clauses where each \(r_{l}\) is either an element of \(S\) or a resolvant of two previous \(r\) 's. (Thus, resolution refutation of \(S\) is just a resolution derivation of \(F\) from \(S .\) ) Show that if there is a resolution derivation of \(\lambda\) from \(S\) and a resolution refutation of \(S \cup\\{\lambda\\},\) then there is a resolution refutation of \(S .\) (e) Prove that if there is a resolution refutation \(\rho\) of \(\left\\{\lambda_{1} \vee \lambda_{2} \vee \ldots \vee \lambda_{k}\right\\} \cup S,\) then either (i) there is a resolution refutation of \(\left.\mid \lambda_{1} \vee \lambda_{2} \vee \cdots \vee \lambda_{k} \vee \lambda_{k+1}\right\\} \cup S\) or (ii) there is a resolution derivation of \(\lambda_{k+1}\) from \(\lambda_{1} \vee \lambda_{2} \vee \ldots \vee \lambda_{k} \vee \lambda_{k+1} \cup S\). (Hint: Prove this by induction on the length \(\rho\). You will have to add \(\lambda_{k+1}\) as a disjunct to some of the clauses in \(\rho\). It is not true in general that if \(S \models \lambda\), then there is a resolution derivation of \(\lambda\) from \(S .\) ) (f) Prove that resolution refutation is complete.

Find at least two different ways to fill in the ellipses in the set descriptions given. For example, \(\\{2,4, \ldots, 12\\}\) could be written either \(\mid 2 n: 1 \leq n \leq 6\) and \(n \in \mathbb{N})\) or \(\mid n+1: n \in\\{1,3,5,7,11\\}\\}\) (a) \([1,3, \ldots, 31)\) (b) \(\\{1,2, \ldots, 26 \mid\) (c) \(\\{2,5, \ldots, 32\\}\)

The second stage of the procedure to "push negations inward" started with a formula whose only logical connectives are \(\neg, v,\) and \(\wedge\) and constructed a tautologically equivalent formula with negations applied only to proposition letters. (a) Write an algorithm describing exactly what is done. The algorithm should work on formulas as strings of symbols. To avoid what in this case is irrelevant detail, the program should assume that all proposition letters are one character long and that any symbol encountered, except for \((.), \wedge, v,\) and \(\neg,\) is a proposition letter. Assume that the formula contains no blanks. (It is perhaps easiest to consider the program as a function that is passed the original formula - a string-as a parameter, and then returns the equivalent formula with all the negations pushed inward. It is casiest to use recursion to handle many subformulas.) (b) Prove that your program from part (a) works. (Hint: if your program in part (a) uses recursion to handle subformulas, it is natural to do this proof by induction on formulas. However, the induction may not be straightforward.)

Let the universe \(U\) be the set of all human beings living in the year \(2001,\) and translate the following English sentences into quantified formulas. Let \(P(x)\) stand for \(" x\) is young" \(Q(x)\) for \(^{4} x\) is female," and \(R(x)\) for \(^{*} x\) is an athlete." (a) "All athletes are young." (b) "Not all young people are athletes." (c) "All young people are not athletes." (Warning: In informal English, this sentence has two quite different meanings. One is "more grammatically correct" than the other, however, and that is the one we're asking for.) (d) "Some young people are not athletes." (e) "Some athletes are young females." (f) "All athletes are young males." (g) "Some athletes are female and are not young." (h) "Some young females are not athletes." (i) "All young females are athletes." (j) "Some athletes are not young." (k) "No young people are athletes." (1) "All athletes are either female or are young." (m) "If all athletes are female, then all athletes are young; otherwise, no athletes are young."

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