(a) In Simulated Annealing, if T2 > T1, is the probability of adopting a new worse state higher in T2 or in T1? Why? (No marks will be given for absent or incorrect explanations.) [5] (b) Does the Simulated Annealing algorithm always terminate? Why or why not? (No marks will be given for absent or incorrect explanations.) [5] (c) A Genetic Algorithm is used to evolve a binary string of length n to one where the sum (from left to right) of the last four genes is equal to 1. The initial population is a randomly generated set of binary strings of length n, such as those shown here: 00110001 01011101 11101111 Give a suitable fitness function for this problem. [10] Activate Go to Settin