A Pacman goal-based agent. I have solved several of these search problems using depth-first search, breadth-first search, uniform cost search, and a star search. A full description of the project can be found in .
The goal of this problem is to navigate through a maze and find one food node. Below is an example of the medium maze:
In the search.py file you can see my execution of these algorithm styles. These are used as agents for pathfinding in the Pacman world.
In the searchAgents.py file, I created problem definitions to encode the state space differently to allow my search algorithms to solve different problems. Such as the find all corners and eat all food. I developed heuristics that increased the efficiency of the A* algorithm.
Another detailed description of the project can be found here: https://inst.eecs.berkeley.edu/~cs188/sp19/project1.html#Q8