# 1. Use the backward component of the dynamic programing algorithm to find another optimal alignment.

1. Use the backward component of the dynamic
programing algorithm to find another optimal alignment of the characters . How
many optimal alignments are there?

2. With the Levenshtein metric of Section 4.1.2, use
dynamic programming to determine the minimum edit distance from source strings
sensation and excitation to target string execution.

3. Give a heuristic that a block-stacking program
might use to solve problems of the form stack block X on block Y. Is it

4. The sliding-tile puzzle consists of three black
tiles, three white tiles, and an empty space in the

1. Use the backward component of the dynamic
programing algorithm to find another optimal alignment of the characters . How
many optimal alignments are there?

2. With the Levenshtein metric of Section 4.1.2, use
dynamic programming to determine the minimum edit distance from source strings
sensation and excitation to target string execution.

3. Give a heuristic that a block-stacking program
might use to solve problems of the form stack block X on block Y. Is it

4. The sliding-tile puzzle consists of three black
tiles, three white tiles, and an empty space in the configuration shown in
Figure 4.29. The puzzle has two legal moves with associated costs: A tile may
move into an adjacent empty location. This has a cost of 1. A tile can hop over
one or two other tiles into the empty position. This has a cost equal to the
number

of tiles jumped over. The goal is to have all the
white tiles to the left of all the black tiles. The position of the blank is
not important.

a. Analyze the state space with respect to
complexity and looping.

b. Propose a heuristic for solving this problem and
analyze it with respect to admissibility, monotonicity, and informedness.

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