Week 3 we studied about informed searches where the search functions are added with a heuristic value. we learned multiple ways to assign a heuristic value but the core concept behind is to relax the question to make it more coherent.
From this we learned algorithm such as the best first search or the greedy algorithm which looks based on only the heuristic value. A* which utilized the actual path is a more optimal way of solving the problems which takes into account actual path as well.
h(n) is only admissible if it is below h(n) otherwise it is false.
We also briefly looked at local search or a part of complete search function. The simplest way was hill climbing. by searching neighbors and checking the most optimal value from close results.
then we got confused about simulated annealing. however we started to understand it better at the end of the lesson. i began to understand it is based on probabilistic statistics and therefore may require further reading.
lastly, we studied about genetic algorithm where trial and error occurs until the best solution is found.