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skeleton.py
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skeleton.py
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# -*- coding: utf-8 -*-
"""
Created on Mon Mar 12 10:52:56 2018
@author: jess
"""
from enum import Enum
import numpy as np
from random import randrange
import string
import random
class Direction(Enum):
up=0
down=1
left=2
right=3
stepsTaken=0
nbMaxSteps=500
Q = {}
gamma=0.95
strat=1
epsilon=0.99
maze=[]
penalty=0
#values of each movement
step=-1
stepTrap=-20
stepExit=500
stepWall=-100
#current position of the robot
position=[0, 0]
#funciton that checks if a certain place in the Q matrix is empty, returns 1 if it is
def currentQEmpty():
global Q
global position
moves=[]
if (position[0]!=0):
moves.append(Direction.left)
if (position[0]!=cols-1):
moves.append(Direction.right)
if (position[1]!=0):
moves.append(Direction.down)
if (position[1]!=rows-1):
moves.append(Direction.up)
for d in moves:
if (Q.get((position[0],position[1],d),'A')=='A'):
return 1
return 0
#intialise the Q matrix
cols=10
rows=10
values=np.zeros((rows,cols))
for x in range(rows):
for y in range(cols):
for dir in Direction:
Q[(x, y, dir)] = 0
#fills the Q matrix (replaces empty values only)
def QFill(moves):
global maze
global position
global Q
global step
global stepTrap
global stepWall
global stepExit
global gamma
for d in moves:
reward=0
newpos=position
if d==Direction.up:
newpos=[position[0], position[1]+1]
if d==Direction.down:
newpos=[position[0], position[1]-1]
if d==Direction.left:
newpos=[position[0]-1, position[1]]
if d==Direction.right:
newpos=[position[0]+1, position[1]]
reward=reward+values[newpos[0],newpos[1]]
if(Q.get((position[0],position[1],d),0)==0):
Q[position[0],position[1],d]=reward
#Qmove: decides which move to make depending on current Q values
#this is where the issue is!
def Qmove(moves):
global position
global Q
global step
global stepTrap
global stepWall
global stepExit
global gamma
bestd=0
newd=moves[random.randint(0,len(moves)-1)]
for d in moves:
newpos=position
if d==Direction.up:
newpos=[position[0], position[1]+1]
if d==Direction.down:
newpos=[position[0], position[1]-1]
if d==Direction.left:
newpos=[position[0]-1, position[1]]
if d==Direction.right:
newpos=[position[0]+1, position[1]]
#update value to best value of new position
if Q.get((newpos[0],newpos[1],d),0)>=Q.get((newpos[0],newpos[1],bestd),0):
bestd=d
Q[position[0],position[1],d]=Q.get((position[0],position[1],d),0)+ (values[newpos[0]][newpos[1]] + gamma * Q.get((newpos[0],newpos[1],bestd),1) - Q.get((position[0],position[1],d),0))
#update arrow
if Q.get((position[0],position[1],d),0)>Q.get((position[0],position[1],newd),0):
newd=d
return newd
#create maze
ch=['0', '1', '3']
for i in range(cols):
maze.append([0]*(cols))
for j in range(cols):
random_index = randrange(0,len(ch))
maze[i][j]=ch[random_index]
if i==cols-1 and j==cols-1:
maze[i][j]='5'
if i==0 and j==0:
maze[i][j]='0'
if(maze[i][j]=="1"):
values[i][j]=step
elif(maze[i][j]=="0"):
values[i][j]=stepWall
elif(maze[i][j]=="3"):
values[i][j]=stepTrap
else:
values[i][j]=stepExit
#move
while(stepsTaken<nbMaxSteps):
moves=[]
#if he finishes he starts over
if(position[0]==rows-1 and position[1]==cols-1):
position[0]=0
position[1]=0
penalty=0
#identify the moves he can legally make
if (position[0]!=0):
moves.append(Direction.left)
if (position[0]!=cols-1):
moves.append(Direction.right)
d=moves[0]
if (position[1]!=0):
moves.append(Direction.down)
if (position[1]!=rows-1):
moves.append(Direction.up)
dest=[]
#choose epsilon value
rand=random.uniform(0, 1)
if(rand<epsilon**stepsTaken):
strat=1
#explore
else:
strat=2
#exploit
#print(epsilon**stepsTaken)
if(currentQEmpty() or strat==1):
QFill(moves)
d=moves[random.randint(0,len(moves)-1)]#how and why he moves
print('dumb')
else:
d=Qmove(moves)
print('smart')
if(d==Direction.left):
dest.append(position[0]-1) #x decreases by 1 place
dest.append(position[1]) #y does not change
if(d==Direction.right):
dest.append(position[0]+1) #x increases by 1 place
dest.append(position[1]) #y does not change
if(d==Direction.up):
dest.append(position[0]) #x does not change&&
dest.append(position[1]+1) #y increases by 1
if(d==Direction.down):
dest.append(position[0]) #x does not change
dest.append(position[1]-1) #y decreases by 1
#penalty is calculated
penalty=penalty+values[dest[0]][dest[1]]
if(maze[dest[0]][dest[1]]!='0'): #not a wall
position=dest
stepsTaken=stepsTaken+1
#show Q matrix
x=position[0]
y=position[1]
print("x:",x," y:",y)
print(" UP:%s" % Q.get((x,y, Direction.up)))
print(" DOWN:%s" % Q.get((x,y, Direction.down)))
print(" LEFT:%s" % Q.get((x,y, Direction.left)))
print(" RIGHT:%s\n" % Q.get((x,y, Direction.right)))