Are all problems in P solvable in a reasonable amount of time? Explain your answer.

Need more elaboration on Dining-Philosophers Problems please.

Describe how duality can be applied to linear programming problems.

Show that (p ∧ q) → r and (p → r) ∧ (q → r) are not logically equivalent, without using truth tables.

7. Please just type the answer.

Please show written work with answer What is the difference between an undecidable problem and an intractable problem

Show that (p ∧ q) → r and (p → r) ∧ (q → r) are not logically equivalent, without using truth tables.

Consider the following NDFSM M, list the first ten elements of L(M) in lexicographic order (shortest first, then alphabetically if same length). b E, a, aa, ab, aaa, aab, baa, bab, aaaa, aaab a, aa, ab, aaa, aab, baa, bab, aaaa, aaab, aaba E, a, aa, ba, aaa, aba, baa, bba, aaaa, aaba a, aa, ba, aaa, aba, baa, bba, aaaa, aaba, aabb

Exercise 2. Here is a classic geometric problem, in the same application domain as the Center Selection problem: Given n points with Cartesian coordinates (₁, 3) in the plane, and positive weights w, find one(!) point (x, y) that minimizes the weighted sum of the Euclidean distances to the given points. For formal clarity: We want to minimize n Σwi i-1 n •√(x- i-1 (x − x)² + (y - y₁)². This problem is at least not very easy to solve exactly. In the following we therefore propose a rough but rather quick and simple approximation algorithm: Instead of the Euclidean distance, take the Manhattan distance and minimize 1 w₁(x − x₂|+|y-yil). 2.1. Explain how the point that minimizes the weigthed sum of Manhattan distances can be found in polynonial time. That is: Sketch an algorithm, argue why it is correct, and explain your time bound. Try to keep the time bound as low as possible. 2.2. Show that this algorithm has an approximation ratio √2. More specifi- cally: The point found by the…

Show the difference in the interaction of rules, data and answers in machine learning and classical programming.