Topic: Informed Search & Local Search

This week we discussed about informed search, which includes algorithms like the A* algorithm and the Greedy Best First Search. We learned how to assign heuristic values, what they mean and how the algorithms we have learned today use them to function.

Another topic that was brought up was the local search, which includes Hill Climbing, Simulated Annealing and the Genetic Algorithm. For this session, the Genetic Algorithm was the one being mainly focused on. From what I noticed, most of the algorithms introduced from local search put in randomness in them for optimization purposes. The Hill Climbing uses randomness by exploring random neighboring nodes to get the optimum result. While the Genetic Algorithm uses mutation in the bit string to get different results.