randomaze
A Random Maze framework to build reinforcent learning players on top of.
Install from GitHub : pip3 install git+git://github.com/sauravkaushik8/randomaze.git
OR
Install from PyPi : pip3 install randomaze
Example:
>>> #Loading Maze from randomaze
>>> from randomaze import Maze
>>>
>>> #Defining a 4X4 Maze - 1: Player, 2: Goal, 3: Pit
>>> obj = Maze(4,4)
>>> obj.print_maze()
[[1. 0. 0. 3.]
[0. 0. 0. 0.]
[0. 2. 0. 0.]
[0. 0. 0. 0.]]
>>>
>>> #Playing a Random series of actions
>>> op = None
>>> while(op == None):
... op = obj.move(take_random_action = True)
... obj.print_maze()
...
Action: Right
Old: 1 1
New: 2 1
[[0. 1. 0. 3.]
[0. 0. 0. 0.]
[0. 2. 0. 0.]
[0. 0. 0. 0.]]
Action: Right
Old: 2 1
New: 3 1
[[0. 0. 1. 3.]
[0. 0. 0. 0.]
[0. 2. 0. 0.]
[0. 0. 0. 0.]]
Action: Down
Old: 3 1
New: 3 2
[[0. 0. 0. 3.]
[0. 0. 1. 0.]
[0. 2. 0. 0.]
[0. 0. 0. 0.]]
Action: Up
Old: 3 2
New: 3 1
[[0. 0. 1. 3.]
[0. 0. 0. 0.]
[0. 2. 0. 0.]
[0. 0. 0. 0.]]
Action: Left
Old: 3 1
New: 2 1
[[0. 1. 0. 3.]
[0. 0. 0. 0.]
[0. 2. 0. 0.]
[0. 0. 0. 0.]]
Action: Right
Old: 2 1
New: 3 1
[[0. 0. 1. 3.]
[0. 0. 0. 0.]
[0. 2. 0. 0.]
[0. 0. 0. 0.]]
Action: Right
Old: 3 1
[[0. 0. 1. 3.]
[0. 0. 0. 0.]
[0. 2. 0. 0.]
[0. 0. 0. 0.]]
>>>
>>> #Printing the Result:
>>> print(op)
Lost!
