def __init__(self):
self.mazeDFS = Maze()
self.free = False
self.goal = []
self.mazeDFS.findEnd(self.goal)
self.start = []
self.mazeDFS.findStart(self.start)
def __init__(self):
self.mazeM = Maze()
self.goal = []
self.mazeM.findEnd(self.goal)
self.start = []
self.mazeM.findStart(self.start)
# Project 1
# Contributors: Logan Garza, Timothy Kempster, Aidan Zastrow
# The problem we addressed in our project was the solving a linear maze in an [x,y] plane using python.
# When traversing in a maze, there are four basic actions you can proceed with at any given point,
# you can check for a wall and attempt to move: right, up, down, or left.
# Our project aimed to automate this decision making based on different algorithms and heuristics.
# We implemented a depth first search algorithm,
# A star heuristic, and greedy best-first heuristic to address different ways to traverse and
# solve a maze given that it has one specific entry point and one specific exit/goal point.
from bin.Maze import Maze
from bin.AStarSolver import AStarSolver
from bin.DfsSolver import DfsSolver
from bin.GreedySolver import GreedySolver
test = Maze()
test2 = AStarSolver()
test3 = DfsSolver()
test4 = GreedySolver()
print("\n")
# Main Body. Runs through all the algorithms.
print("Start of DFS Solver")
print("Original Maze: 1 = wall, 0 = free, 2 = start, 3 = exit, X = visited")
test3.printDfsMaze()
print()
print("Printing locations visited by the solver in form of [x, y]")
test3.solve(test3.start[1], test3.start[0])
print("Finished Maze:")
test3.printDfsMaze()
print("End of DFS Solver\n")
print("Start of Greedy Solver")