BFS and DFS AI Path Search - Part 1

Data Science, AI and ML
1 
import sys

class Node():
    def __init__(self, state, parent, action):
        self.state = state
        self.parent = parent
        self.action = action


class StackFrontier():
    def __init__(self):
        self.frontier = []

    def add(self, node):
        self.frontier.append(node)

    def contains_state(self, state):
        return any(node.state == state for node in self.frontier)

    def empty(self):
        return len(self.frontier) == 0

    def remove(self):
        if self.empty():
            raise Exception("empty frontier")
        else:
            node = self.frontier[-1]
            self.frontier = self.frontier[:-1]
            return node


class QueueFrontier(StackFrontier):

    def remove(self):
        if self.empty():
            raise Exception("empty frontier")
        else:
            node = self.frontier[0]
            self.frontier = self.frontier[1:]
            return node
2

Sample Input Files: Please use them after reading part 5 only

maze1.txt

#####B#
##### #
####  #
#### ##
     ##
A######

maze2.txt

###                 #########
#   ###################   # #
# ####                # # # #
# ################### # # # #
#                     # # # #
##################### # # # #
#   ##                # # # #
# # ## ### ## ######### # # #
# #    #   ##B#         # # #
# # ## ################ # # #
### ##             #### # # #
### ############## ## # # # #
###             ##    # # # #
###### ######## ####### # # #
###### ####             #   #
A      ######################

maze2.txt

##    #
## ## #
#B #  #
# ## ##
     ##
A######