Effective AI for one player-one ghost pacman
This is an adversarial game problem where you need to find the optimal behavior from each position. There are several approaches to attack such problem.

You can do Minimax with alpha beta pruning to find the best move.
It will provide you an optimal move after exploring the entire tree up to some level (not too deep if the branching factor is too high, here your branching factor is $4*players$) using a handcrafted heuristic by you. So the quality of the results heavily depends on the quality of the heuristic. If you improve the pruning you can achieve better results, as you can explore more.

Another approach is Montecarlo Tree Search. This algorithms performs really good in several games, and doesn't depend on any previously knowledge of the game. Roughly speaking, it seeks the best option by expanding the tree from the state you are in and calculates the quality of a state by performing a random simulation of the game.

There is a novel approach, Reinforcement learning, that you can use to find the answer. The idea behind it is approximate the optimal policy that gives you the maximal reward. Here you can understand by policy the action you will make at any position an the rewards are the points you get after each action. You can read more about it here.