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initial commit, testing only

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sp 1 year ago
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  1. 71
      first_try.prism
  2. 78
      test.py
  3. 78
      test_model.py

71
first_try.prism
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mdp
const int initY = 40;
const int initX = 80;
const int maxY = 240;
const int minX = 12;
const int maxX = 147;
formula HitTree = (122<x & x<139) & (220<y & y=232);
formula HitGate = ((x=51 | x=79) & y=164);
formula PassedGates = (158<y & y<165 & 51<x & x<79);
global move : [0..3] init 0;
module skier
ski_position : [1..14] init 8;
done : bool init false;
[left] !done & move=0 & ski_position>1 -> (ski_position'=ski_position-1) & (move'=1) & (done'=(PassedGates|HitTree|HitGate));
[right] !done & move=0 & ski_position<14 -> (ski_position'=ski_position+1) & (move'=1) & (done'=(PassedGates|HitTree|HitGate));
[noop] !done & move=0 -> (move'=1) & (done'=(PassedGates|HitTree|HitGate));
[left] done & move=0 & ski_position>1 -> (ski_position'=ski_position-1) & (move'=1);
[right] done & move=0 & ski_position<14 -> (ski_position'=ski_position+1) & (move'=1);
[noop] done & move=0 -> (move'=1);
endmodule
module updateY
y : [initY..maxY] init initY;
standstill : [0..8] init 0;
[update_y] move=1 & (ski_position=1 | ski_position = 14) & standstill>=5 -> (y'=y) & (standstill'=min(8,standstill+1)) & (move'=2);
[update_y] move=1 & (ski_position=1 | ski_position = 14) & standstill<5 -> (y'=min(maxY,y+4)) & (standstill'=min(8,standstill+1)) & (move'=2);
[update_y] move=1 & (ski_position=2 | ski_position = 3 | ski_position = 12 | ski_position = 13) -> (y'=min(maxY,y+8)) & (standstill'=0) & (move'=2);
[update_y] move=1 & (ski_position=4 | ski_position = 5 | ski_position = 10 | ski_position = 11) -> (y'=min(maxY,y+12)) & (standstill'=0) & (move'=2);
[update_y] move=1 & (ski_position=6 | ski_position = 7 | ski_position = 8 | ski_position = 9) -> (y'=min(maxY,y+16)) & (standstill'=0) & (move'=2);
endmodule
module updateX
x : [minX..maxX] init initX;
[update_x] move=2 & standstill>=8 -> (move'=0);
[update_x] move=2 & standstill<8 & (ski_position=7 | ski_position=8) -> (move'=0);
[update_x] move=2 & standstill<8 & ski_position=6 -> 0.1: (x'=max(minX,x-3)) + 0.7: (x'=max(minX,x-4)) + 0.2: (x'=max(minX,x-5)) & (move'=0);
[update_x] move=2 & standstill<8 & ski_position=9 -> 0.1: (x'=min(maxX,x+3)) + 0.7: (x'=min(maxX,x+4)) + 0.2: (x'=min(maxX,x+5)) & (move'=0);
[update_x] move=2 & standstill<8 & (ski_position=4 | ski_position=5) -> 0.1: (x'=max(minX,x-5)) + 0.7: (x'=max(minX,x-6)) + 0.2: (x'=max(minX,x-7)) & (move'=0);
[update_x] move=2 & standstill<8 & (ski_position=10 | ski_position=11) -> 0.1: (x'=min(maxX,x+5)) + 0.7: (x'=min(maxX,x+6)) + 0.2: (x'=min(maxX,x+7)) & (move'=0);
[update_x] move=2 & standstill<8 & (ski_position=2 | ski_position=3) -> 0.1: (x'=max(minX,x-5)) + 0.7: (x'=max(minX,x-6)) + 0.2: (x'=max(minX,x-7)) & (move'=0);
[update_x] move=2 & standstill<8 & (ski_position=12 | ski_position=13) -> 0.1: (x'=min(maxX,x+5)) + 0.7: (x'=min(maxX,x+6)) + 0.2: (x'=min(maxX,x+7)) & (move'=0);
[update_x] move=2 & standstill<8 & (ski_position=1) -> 0.1: (x'=max(minX,x-0)) + 0.7: (x'=max(minX,x-2)) + 0.2: (x'=max(minX,x-3)) & (move'=0);
[update_x] move=2 & standstill<8 & (ski_position=14) -> 0.1: (x'=min(maxX,x+0)) + 0.7: (x'=min(maxX,x+2)) + 0.2: (x'=min(maxX,x+3)) & (move'=0);
endmodule
rewards
[left] !done & PassedGates : 100;
[right] !done & PassedGates : 100;
[noop] !done & PassedGates : 100;
[left] !done & (HitTree) : -200;
[right] !done & (HitTree) : -200;
[noop] !done & (HitTree) : -200;
[left] !done & (HitGate) : -150;
[right] !done & (HitGate) : -150;
[noop] !done & (HitGate) : -150;
endrewards

78
test.py
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import gym
from PIL import Image
from copy import deepcopy
import numpy as np
from matplotlib import pyplot as plt
import readchar
import queue
ski_position_queue = queue.Queue()
env = gym.make("ALE/Skiing-v5", render_mode="human")
observation, info = env.reset()
y = 40
standstillcounter = 0
def update_y(y, ski_position):
global standstillcounter
if ski_position in [6,7, 8,9]:
standstillcounter = 0
y_update = 16
elif ski_position in [4,5, 10,11]:
standstillcounter = 0
y_update = 12
elif ski_position in [2,3, 12,13]:
standstillcounter = 0
y_update = 8
elif ski_position in [1, 14] and standstillcounter >= 5:
if standstillcounter >= 8:
print("!!!!!!!!!! no more x updates!!!!!!!!!!!")
y_update = 0
elif ski_position in [1, 14]:
y_update = 4
if ski_position in [1, 14]:
standstillcounter += 1
return y_update
def update_ski_position(ski_position, action):
if action == 0:
return ski_position
elif action == 1:
return min(ski_position+1, 14)
elif action == 2:
return max(ski_position-1, 1)
approx_x_coordinate = 80
ski_position = 8
for _ in range(1000000):
action = env.action_space.sample() # agent policy that uses the observation and info
action = int(repr(readchar.readchar())[1])
ski_position = update_ski_position(ski_position, action)
y_update = update_y(y, ski_position)
y += y_update if y_update else 0
old_x = deepcopy(approx_x_coordinate)
approx_x_coordinate = int(np.mean(np.where(observation[:,:,1] == 92)[1]))
print(f"Action: {action},\tski position: {ski_position},\ty_update: {y_update},\ty: {y},\tx: {approx_x_coordinate},\tx_update:{approx_x_coordinate - old_x}")
observation, reward, terminated, truncated, info = env.step(action)
if terminated or truncated:
observation, info = env.reset()
observation, reward, terminated, truncated, info = env.step(0)
observation, reward, terminated, truncated, info = env.step(0)
observation, reward, terminated, truncated, info = env.step(0)
observation, reward, terminated, truncated, info = env.step(0)
#plt.imshow(observation)
#plt.show()
#im = Image.fromarray(observation)
#im.save("init.png")
env.close()

78
test_model.py
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import time, re, sys, csv, os
from subprocess import call
from os import listdir, system
from os.path import isfile, join, getctime
from dataclasses import dataclass, field
ski_position_to_rgb_map = {1: "230, 138, 0",
2: "255,153,0",
3: "255, 184, 77",
4: "255, 194, 100",
5: "255, 194, 120",
6: "255, 210, 130",
7: "255, 210, 140",
8: "230, 204, 255",
9: "204, 153, 255",
10: "255, 102, 179",
11: "255, 51, 153",
12: "255, 0, 255",
13: "179, 0, 179",
14: "102, 0, 102"}
def convert(tuples):
return dict(tuples)
@dataclass(frozen=True)
class State:
x: int
y: int
ski_position: int
def default_value():
return {'action' : None, 'choiceValue' : None}
@dataclass(frozen=True)
class StateValue:
ranking: float
choices: dict = field(default_factory=default_value)
def exec(command):
print(f"Executing {command}")
system(f"echo {command} >> list_of_exec")
return system(command)
def fillStateRanking(file_name, match=""):
state_ranking = dict()
try:
with open(file_name, "r") as f:
file_content = f.readlines()
for line in file_content:
if match and skip_line.match(line): continue
stateMapping = convert(re.findall(r"([a-zA-Z_]*[a-zA-Z])=(\d+)?", line))
#print("stateMapping", stateMapping)
choices = convert(re.findall(r"[a-zA-Z_]*(left|right|noop)[a-zA-Z_]*:(-?\d+\.?\d*)", line))
#print("choices", choices)
ranking_value = float(re.search(r"Value:([+-]?(\d*\.\d+)|\d+)", line)[0].replace("Value:",""))
#print("ranking_value", ranking_value)
state = State(int(stateMapping["x"]), int(stateMapping["y"]), int(stateMapping["ski_position"]))
value = StateValue(ranking_value, choices)
state_ranking[state] = value
return state_ranking
except EnvironmentError:
print("TODO file not available. Exiting.")
sys.exit(1)
ranking = fillStateRanking("action_ranking")
sorted_ranking = sorted(ranking.items(), key=lambda x: x[1].ranking)
draw_commands = list()
for state in sorted_ranking[-20:-1]:
print(state)
x = state[0].x
y = state[0].y
markerSize = 2
print(state[0].ski_position)
draw_commands.append(f"-fill 'rgba({ski_position_to_rgb_map[state[0].ski_position]},0.7)' -draw 'rectangle {x-markerSize},{y-markerSize} {x+markerSize},{y+markerSize} '")
command = f"convert init.png {' '.join(draw_commands)} first_try.png"
exec(command)
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