Please answer all questions!

Describe Hill-Climbing Search [0.25]. Please explain why standard hill climbing algorithm suffers from the local maxima (or local minima) problem [0.25 pt] 1. Describe simulated annealing search [0.25 pt]. If T-0 at all times, which search method is the simulated annealing search equivalent to [0.25]? 2. 3. Assume you were asked to place 8 queens on an 8x8 chessboard such that no two queens can attack each other (i.e. share the same row, column, or diagonal) Please introduce a solution to use genetic algorithm to solve the game. Please explain the encoding of the state for genetic algorithm (i.e., the representation of the chromosome), the fitness function, the cross over, and the mutation process. [1 pt] Figure 1 shows the current layout of a tic-tac-toe game board, and Max ("X") is going to make the next move. Please draw the remaining states of the game tree [0.5 pt], and explain what is the best move for Max [0.5 pt] 4. XX's turn (MAX) Figure 1 Describe Hill-Climbing Search [0.25]. Please explain why standard hill climbing algorithm suffers from the local maxima (or local minima) problem [0.25 pt] 1. Describe simulated annealing search [0.25 pt]. If T-0 at all times, which search method is the simulated annealing search equivalent to [0.25]? 2. 3. Assume you were asked to place 8 queens on an 8x8 chessboard such that no two queens can attack each other (i.e. share the same row, column, or diagonal) Please introduce a solution to use genetic algorithm to solve the game. Please explain the encoding of the state for genetic algorithm (i.e., the representation of the chromosome), the fitness function, the cross over, and the mutation process. [1 pt] Figure 1 shows the current layout of a tic-tac-toe game board, and Max ("X") is going to make the next move. Please draw the remaining states of the game tree [0.5 pt], and explain what is the best move for Max [0.5 pt] 4. XX's turn (MAX) Figure 1