Another analogous method that utilizes dynamic programming is as follows. Let’s consider a number N representing the digits. We will establish a lookup table initialized with a count of one for each digit from 0 to 9. If N=1, the outcome will be the total of all count values in the lookup table. For N >= 2, we will adjust the count for each digit based on its neighboring digits and continue this process for N iterations. After each iteration, the lookup table will be refreshed with new count values. The aggregated count values following N iterations will represent the total number of possible combinations. For instance, if N=2, after the first update, our lookup table will have the counts adjusted as follows: 0 - 1, 1 - 3 (1 can move to 2, 4, and itself), 2 - 4 (2 can move to 3, 1, 5, and itself), and so forth.. After the second iteration, our lookup table will be further updated to: 0 - 2 (from 1 and itself), 1 - 4 (from 2, 3, 5, and itself), 2 - 7 (from 1, 0, 3, 4, 5, 6, and itself) The total number of possible combinations will be the sum of the values in the lookup table after 2 iterations.