This imaginary firm uses Kerberos. Do you have a strategy if the AS or TGS suddenly stops working?

Please explain the answer and explain how to do it!! f10

Give the required conditions for a stalemate to occur

Correct answer will be upvoted else Multiple Downvoted. Computer science.     All sections between two houses will be shut, in case there are no instructors in the two of them. Any remaining sections will remain open.    It ought to be feasible to go between any two houses utilizing the underground sections that are open.    Educators ought not reside in houses, straightforwardly associated by an entry.    Kindly assist the coordinators with picking the houses where educators will reside to fulfill the security necessities or establish that it is unimaginable.    Input    The originally input line contains a solitary integer t — the number of experiments (1≤t≤105).    Each experiment begins with two integers n and m (2≤n≤3⋅105, 0≤m≤3⋅105) — the number of houses and the number of sections.    Then, at that point, m lines follow, every one of them contains two integers u and v (1≤u,v≤n, u≠v), depicting a section between the houses u and v. It is ensured that there are no two sections…

Can you find a stable outcome for the following network, if possible. If not, please explain why.

In other words, "Could you provide a summary of Classical optimization strategies?"

If we want to avoid a stalemate, what are the key differences between those two strategies?

You are required to create a Julia program that does the following in this problem:Analyze every policy you are given, then tweak it until a solution is discovered. Real-time recording and saving of the Markov decision process (MDP).

no need for a complete solution. I just need a simple solution with the correct answer. downvote if it is incorrect. skip if you already did this or else get a downvote.

Q.1: a. What is TFIDF? What is significance of IDF? Explain role of IDF in classification with one real life example. Give an example where IDF may not make sense while classifying. b. Explain how can you apply TFIDF to classify product reviews? (Here each post has 20 words). Give Pseudo code for the same. c. Discuss an algorithm to rank these reviews for different new customers based on their personalized parameters. (Make necessary assumptions) d. Can you combine CNN and TFIDF in this case? How? e. Discuss an algorithm where you combine different reviews to provide a single personalized review of the product for a particular customer.