2. (Basic) The Weighted Interval Selection problem generalizes its unweighted version. Namely, in the weighted setting, each interval / has weight w, > 0, and the goal is to choose a max-weight subset of mutually disjointon-overlapping intervals. For the unweighted version, we had the following recursion: the following recursionn if i 0 otherwise, max(M(j) +1,M(i-1)) where I, is the interval with the largest finish time that ends before I starts. Here, M i) I(THI 4?? ilu:111axinluin number of inilinally di:1' 'ini ini crval:; lhai call ba, cll.XX.RA from Io, 11, I2,.., /i. Adapt this recursion to the weighted setting. 2. (Basic) The Weighted Interval Selection problem generalizes its unweighted version. Namely, in the weighted setting, each interval / has weight w, > 0, and the goal is to choose a max-weight subset of mutually disjointon-overlapping intervals. For the unweighted version, we had the following recursion: the following recursionn if i 0 otherwise, max(M(j) +1,M(i-1)) where I, is the interval with the largest finish time that ends before I starts. Here, M i) I(THI 4?? ilu:111axinluin number of inilinally di:1' 'ini ini crval:; lhai call ba, cll.XX.RA from Io, 11, I2,.., /i. Adapt this recursion to the weighted setting