2) 5 Let P(A) = 2. Calculate the upper bound for P(U A;) using union bound (rounded to 3 decimal places). O 0.937 0.984 ○ 0.969 1 i=1 3) Which of the following is/are the shortcomings of TD Learning that Q-learning resolves? UTD learning cannot provide values for (state, action) pairs, limiting the ability to extract an optimal policy directly ☐ TD learning requires knowledge of the reward and transition functions, which is not always available ☐ TD learning is computationally expensive and slow compared to Q-learning TD learning often suffers from high variance in value estimation, leading to unstable learning TD learning cannot handle environments with continuous state and action spaces effectively

Correct answer will be upvoted else downvoted. Computer science.    deck is called arranged if the front qualities are in expanding request and the back qualities are in diminishing request. That is, if ai<ai+1 and bi>bi+1 for all 1≤i<n.    To flip a card I implies trading the upsides of simulated intelligence and bi. You should flip some subset of cards (perhaps, none), then, at that point, put every one of the cards in any request you like. What is the base number of cards you should flip to sort the deck?    Input    The main line contains a solitary integer n (1≤n≤2⋅105) — the number of cards.    The following n lines depict the cards. The I-th of these lines contains two integers ai,bi (1≤ai,bi≤2n). Each integer somewhere in the range of 1 and 2n shows up precisely once.    Output    In case it is difficult to sort the deck, output "- 1". In any case, output the base number of flips needed to sort the deck.