Merge pull request 'Merge genetic2 to final_show' (#27) from genetic2 into final_show
Reviewed-on: #27
This commit is contained in:
commit
b78f7f5ee7
2
App.py
2
App.py
@ -85,7 +85,7 @@ def init_demo(): #Demo purpose
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print_to_console("Traktor porusza sie obliczona sciezka BFS")
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traktor.move_by_root(bfsRoot2, pole, [traktor.irrigateSlot])
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if(bfs3_flag):
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bfsRoot3 = BFS.BFS3({'x': 0, 'y': 0, 'direction': "E"})
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bfsRoot3 = BFS.BFS3({'x': 0, 'y': 0, 'direction': "E"},goalTreasure)
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#displayControler: NUM_X: 20, NUM_Y: 12 (skarb) CHANGE THIS IN DCON BY HAND!!!!!!!!
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bfsRoot3.reverse()
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print_to_console("Traktor porusza sie obliczona sciezka BFS")
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2
BFS.py
2
BFS.py
@ -134,7 +134,7 @@ def check3(tab, state):
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def BFS3(istate,GT):
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randomGT=True
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randomGT=False
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if(randomGT==True):
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goalTreassuere = (random.randint(0,NUM_X-1), random.randint(0,NUM_Y-1))
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else:
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139
GeneticAccuracy.py
Normal file
139
GeneticAccuracy.py
Normal file
@ -0,0 +1,139 @@
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import json
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import random
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from displayControler import NUM_Y, NUM_X
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iterat = 2500
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population = 120
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roulette = True
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plants = ['corn', 'potato', 'tomato', 'carrot']
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initial_yields = {'corn': 38, 'potato': 40, 'tomato': 43, 'carrot': 45}
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yield_reduction = {
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'corn': {'corn': -4.5, 'potato': -3, 'tomato': -7, 'carrot': -7},
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'potato': {'corn': -7, 'potato': -5, 'tomato': -10, 'carrot': -6},
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'tomato': {'corn': -4, 'potato': -5, 'tomato': -7, 'carrot': -7},
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'carrot': {'corn': -11, 'potato': -5, 'tomato': -4, 'carrot': -7}
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}
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yield_reduction2 = {
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'corn': {'corn': None, 'potato': -4, 'tomato': -2, 'carrot': -4},
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'potato': {'corn': None, 'potato': -5, 'tomato': -5, 'carrot': -2},
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'tomato': {'corn': -5, 'potato': -3, 'tomato': -7, 'carrot': None},
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'carrot': {'corn': -3, 'potato': -6, 'tomato': -4, 'carrot': -9}
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}
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yield_multiplier = {'corn': 1.25, 'potato': 1.17, 'tomato': 1.22, 'carrot': 1.13}
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yield_multiplier2 = {'corn': 1.25, 'potato': 1.19, 'tomato': 1.22, 'carrot': 1.15}
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def calculate_yields(garden):
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rows = len(garden)
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cols = len(garden[0])
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total_yields = 0
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for i in range(rows):
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for j in range(cols):
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plant = garden[i][j]
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yield_count = initial_yields[plant]
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# Sprawdzanie sąsiadów
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neighbors = [
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(i - 1, j), (i + 1, j), (i, j - 1), (i, j + 1)
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]
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for ni, nj in neighbors:
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if 0 <= ni < rows and 0 <= nj < cols:
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neighbor_plant = garden[ni][nj]
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yield_count += yield_reduction[plant][neighbor_plant]
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yield_count *= yield_multiplier[plant]
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total_yields += yield_count
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return total_yields
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def calculate_yields2(garden):
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rows = len(garden)
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cols = len(garden[0])
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total_yields = 0
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for i in range(rows):
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for j in range(cols):
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plant = garden[i][j]
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yield_count = initial_yields[plant]
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# Sprawdzanie sąsiadów
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neighbors = [
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(i - 1, j), (i + 1, j), (i, j - 1), (i, j + 1)
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]
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neighbor_flag = False
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for ni, nj in neighbors:
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if 0 <= ni < rows and 0 <= nj < cols:
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neighbor_plant = garden[ni][nj]
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if yield_reduction2[plant][neighbor_plant] is not None: # jeśli jest wartość None to plony dla tej rośliny będą wyzerowane
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yield_count += yield_reduction2[plant][neighbor_plant]
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else:
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neighbor_flag = True
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if not neighbor_flag:
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yield_count *= yield_multiplier2[plant]
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total_yields += yield_count
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return total_yields
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def generate_garden(rows=20, cols=12):
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return [[random.choice(plants) for _ in range(cols)] for _ in range(rows)]
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def generate_garden_with_yields(t, rows=NUM_Y, cols=NUM_X):
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garden = generate_garden(rows, cols)
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if t == 1:
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total_yields = calculate_yields(garden)
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else:
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total_yields = calculate_yields2(garden)
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return [garden, total_yields]
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def generate():
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s1 = 0
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s2 = 0
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n = 150
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for i in range(n):
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x = generate_garden_with_yields(1)
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s1 += x[1]
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y = generate_garden_with_yields(2)
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s2 += y[1]
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return [s1/n, s2/n]
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data = generate()
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# print(data)
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# Odczyt z pliku
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with open(f'pole_pop{population}_iter{iterat}_{roulette}.json', 'r') as file:
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garden_data = json.load(file)
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# print("Odczytane dane ogrodu:")
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# for row in garden_data:
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# print(row)
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print("Wygenerowane przy pomocy GA: ", calculate_yields(garden_data))
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print(f"Przeciętny ogród wygenerowany randomowo ma {data[0]} plonów")
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print("Uśredniony przyrost plonów (ile razy więcej plonów): ", calculate_yields(garden_data)/data[0])
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# Odczyt z pliku
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with open(f'pole2_pop{population}_iter{iterat}_{roulette}.json', 'r') as file:
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garden_data2 = json.load(file)
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# print("Odczytane dane ogrodu:")
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# for row in garden_data2:
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# print(row)
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print("Wygenerowane: przy pomocy GA2", calculate_yields2(garden_data2))
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print(f"Przeciętny ogród wygenerowany randomowo ma {data[1]} plonów")
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print("Uśredniony przyrost plonów (ile razy więcej plonów): ", calculate_yields2(garden_data2)/data[1])
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@ -136,7 +136,7 @@ if __name__ == '__main__':
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roulette = True
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attemps = 150
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iterat = 2500
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population = 100
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population = 120
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best = []
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for a in range(attemps):
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generation = generate(population)
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213
GeneticAlgorithm2.py
Normal file
213
GeneticAlgorithm2.py
Normal file
@ -0,0 +1,213 @@
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import copy
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import json
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import random
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from displayControler import NUM_X, NUM_Y
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# Definiowanie stałych dla roślin i plonów
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plants = ['corn', 'potato', 'tomato', 'carrot']
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initial_yields = {'corn': 38, 'potato': 40, 'tomato': 43, 'carrot': 45}
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yield_reduction = {
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'corn': {'corn': None, 'potato': -4, 'tomato': -2, 'carrot': -4},
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'potato': {'corn': None, 'potato': -5, 'tomato': -5, 'carrot': -2},
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'tomato': {'corn': -5, 'potato': -3, 'tomato': -7, 'carrot': None},
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'carrot': {'corn': -3, 'potato': -6, 'tomato': -4, 'carrot': -9}
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}
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yield_multiplier = {'corn': 1.25, 'potato': 1.19, 'tomato': 1.22, 'carrot': 1.15}
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# Generowanie listy 20x12 z losowo rozmieszczonymi roślinami
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def generate_garden(rows=20, cols=12):
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return [[random.choice(plants) for _ in range(cols)] for _ in range(rows)]
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# Funkcja do obliczania liczby plonów
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def calculate_yields(garden):
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rows = len(garden)
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cols = len(garden[0])
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total_yields = 0
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for i in range(rows):
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for j in range(cols):
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plant = garden[i][j]
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yield_count = initial_yields[plant]
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# Sprawdzanie sąsiadów
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neighbors = [
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(i - 1, j), (i + 1, j), (i, j - 1), (i, j + 1)
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]
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neighbor_flag = False
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for ni, nj in neighbors:
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if 0 <= ni < rows and 0 <= nj < cols:
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neighbor_plant = garden[ni][nj]
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if yield_reduction[plant][neighbor_plant] is not None: # jeśli jest wartość None to plony dla tej rośliny będą wyzerowane
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yield_count += yield_reduction[plant][neighbor_plant]
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else:
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neighbor_flag = True
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if not neighbor_flag:
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yield_count *= yield_multiplier[plant]
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total_yields += yield_count
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return total_yields
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# Funkcja do generowania planszy/ogrodu i zapisywania go jako lista z liczbą plonów
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def generate_garden_with_yields(rows=NUM_Y, cols=NUM_X):
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garden = generate_garden(rows, cols)
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total_yields = calculate_yields(garden)
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return [garden, total_yields]
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# Funkcja do generowania linii cięcia i zapisywania jej jako liczba roślin w kolumnie z pierwszej planszy/ogrodu
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def line():
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path = []
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flag = False
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x = random.randint(4, 8)
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position = (0, x)
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path.append(position)
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while not flag: # wybór punktu dopóki nie wybierze się skrajnego
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# prawdopodobieństwo "ruchu" -> 0.6: w prawo, 0.2: w góre, 0.2: w dół
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p = [(position[0] + 1, position[1]), (position[0], position[1] + 1), (position[0], position[1] - 1)]
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w = [0.6, 0.2, 0.2]
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position2 = random.choices(p, w)[0]
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if position2 not in path: # sprawdzenie czy dany punkt nie był już wybrany aby nie zapętlać się
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path.append(position2)
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position = position2
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if position[0] == NUM_X or position[1] == 0 or position[1] == NUM_Y: # sprawdzenie czy osiągnięto skrajny punkt
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flag = True
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info = [] # przeformatowanie sposobu zapisu na liczbę roślin w kolumnie, które będzię się dzidziczyło z pierwszej planszy/ogrodu
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for i in range(len(path) - 1):
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if path[i + 1][0] - path[i][0] == 1:
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info.append(NUM_Y - path[i][1])
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if len(info) < NUM_X: # uzupełnienie informacji o dziedziczeniu z planszy/ogrodu
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if path[-1:][0][1] == 0:
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x = NUM_Y
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else:
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x = 0
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while len(info) < NUM_X:
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info.append(x)
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# return path, info
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return info
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# Funkcja do generowania potomstwa
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def divide_gardens(garden1, garden2):
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info = line()
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new_garden1 = [[] for _ in range(NUM_Y)]
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new_garden2 = [[] for _ in range(NUM_Y)]
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for i in range(NUM_X):
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for j in range(NUM_Y):
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# do utworzonych kolumn w nowych planszach/ogrodach dodajemy dziedziczone rośliny
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if j < info[i]:
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new_garden1[j].append(garden1[j][i])
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new_garden2[j].append(garden2[j][i])
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else:
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new_garden1[j].append(garden2[j][i])
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new_garden2[j].append(garden1[j][i])
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return [new_garden1, calculate_yields(new_garden1)], [new_garden2, calculate_yields(new_garden2)]
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# Funkcja do mutacji danej planszy/ogrodu
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def mutation(garden, not_used):
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new_garden = copy.deepcopy(garden)
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for i in range(NUM_X):
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x = random.randint(0, 11) # wybieramy, w którym wierszu w i-tej kolumnie zmieniamy roślinę na inną
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other_plants = [plant for plant in plants if plant != new_garden[x][i]]
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new_garden[x][i] = random.choice(other_plants)
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return [new_garden, calculate_yields(new_garden)]
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# Funkcja do generowania pierwszego pokolenia
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def generate(n):
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generation = []
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for i in range(n * 3):
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generation.append(generate_garden_with_yields())
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generation.sort(reverse=True, key=lambda x: x[1])
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return generation[:n]
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# Funkcja do implementacji ruletki (sposobu wyboru) - sumuje wszystkie plony generacji
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def sum_yields(x):
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s = 0
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for i in range(len(x)):
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s += x[i][1]
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return s
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if __name__ == '__main__':
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roulette = True
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attemps = 20
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iterat = 2500
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population = 120
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best = []
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for a in range(attemps):
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generation = generate(population)
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print(generation[0][1])
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for i in range(iterat): # ile iteracji - nowych pokoleń
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print(a, i)
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new_generation = generation[:(population // 7)] # dziedziczenie x najlepszych osobników
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j = 0
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while j < (
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population - (
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population // 7)): # dobór reszty osobników do pełnej liczby populacji danego pokolenia
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if roulette: # zasada ruletki -> "2 rzuty kulką"
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s = sum_yields(generation) # suma wszystkich plnów całego pokolenia
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z = []
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if s == 0: # wtedy każdy osobnik ma takie same szanse
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z.append(random.randint(0, population - 1))
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z.append(random.randint(0, population - 1))
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else:
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weights = [] # wagi prawdopodobieństwa dla każdego osobnika generacji
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pos = [] # numery od 0 do 49 odpowiadające numerom osobnikom w generacji
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for i in range(population):
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weights.append(generation[i][1] / s)
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pos.append(i)
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z.append(random.choices(pos, weights)[0]) # wybranie osobnika według wag prawdopodobieństwa
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z.append(random.choices(pos, weights)[0]) # wybranie osobnika według wag prawdopodobieństwa
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else: # metoda rankingu
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z = random.sample(range(0, int(population // 1.7)), 2)
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# krzyzowanie 90% szans, mutacja 10% szans
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function = [divide_gardens, mutation]
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weight = [0.9, 0.1]
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fun = random.choices(function, weight)[0]
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h = fun(generation[z[0]][0], generation[z[1]][0])
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if len(h[0]) == 2:
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new_generation.append(h[0])
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new_generation.append(h[1])
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j += 2
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else:
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new_generation.append(h)
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j += 1
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new_generation.sort(reverse=True, key=lambda x: x[1]) # sortowanie malejąco listy według wartości plonów
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generation = new_generation[:population]
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best.append(generation[0])
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best.sort(reverse=True, key=lambda x: x[1])
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# Zapis do pliku
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||||
# for i in range(len(best)):
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# print(best[i][1], calculate_yields(best[i][0]))
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#
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#
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||||
# with open(f'pole2_pop{population}_iter{iterat}_{roulette}.json', 'w') as file: # zapis planszy/ogrodu do pliku json
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# json.dump(best[0][0], file, indent=4)
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#
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||||
# print("Dane zapisane do pliku")
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#
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# Odczyt z pliku
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# with open(f'pole2_pop{population}_iter{iterat}_{roulette}.json', 'r') as file:
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# garden_data = json.load(file)
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#
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# print("Odczytane dane ogrodu:")
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# for row in garden_data:
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# print(row)
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#
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# print(calculate_yields(garden_data))
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# if best[0][0] == garden_data:
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# print("POPRAWNE: ", calculate_yields(garden_data), calculate_yields(best[0][0]))
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211
GeneticAlgorithm3.py
Normal file
211
GeneticAlgorithm3.py
Normal file
@ -0,0 +1,211 @@
|
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import copy
|
||||
import json
|
||||
import random
|
||||
from displayControler import NUM_X, NUM_Y
|
||||
|
||||
# Definiowanie stałych dla roślin i plonów
|
||||
plants = ['corn', 'potato', 'tomato', 'carrot']
|
||||
initial_yields = {'corn': 38, 'potato': 40, 'tomato': 43, 'carrot': 45}
|
||||
yield_reduction = {
|
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'corn': {'corn': None, 'potato': 0, 'tomato': 0, 'carrot': 0},
|
||||
'potato': {'corn': None, 'potato': 0, 'tomato': 0, 'carrot': 0},
|
||||
'tomato': {'corn': 0, 'potato': 0, 'tomato': 0, 'carrot': None},
|
||||
'carrot': {'corn': 0, 'potato': 0, 'tomato': 0, 'carrot': 0}
|
||||
}
|
||||
yield_multiplier = {'corn': 1.25, 'potato': 1.19, 'tomato': 1.22, 'carrot': 1.13}
|
||||
|
||||
|
||||
# Generowanie listy 20x12 z losowo rozmieszczonymi roślinami
|
||||
def generate_garden(rows=20, cols=12):
|
||||
return [[random.choice(plants) for _ in range(cols)] for _ in range(rows)]
|
||||
|
||||
|
||||
# Funkcja do obliczania liczby plonów
|
||||
def calculate_yields(garden):
|
||||
rows = len(garden)
|
||||
cols = len(garden[0])
|
||||
|
||||
total_yields = 0
|
||||
|
||||
for i in range(rows):
|
||||
for j in range(cols):
|
||||
plant = garden[i][j]
|
||||
|
||||
# Sprawdzanie sąsiadów
|
||||
neighbors = [
|
||||
(i - 1, j), (i + 1, j), (i, j - 1), (i, j + 1)
|
||||
]
|
||||
neighbor_flag = False
|
||||
for ni, nj in neighbors:
|
||||
if 0 <= ni < rows and 0 <= nj < cols:
|
||||
neighbor_plant = garden[ni][nj]
|
||||
|
||||
if yield_reduction[plant][neighbor_plant] is None: # jeśli jest wartość None to plony dla tej rośliny będą wyzerowane
|
||||
neighbor_flag = True
|
||||
|
||||
if not neighbor_flag:
|
||||
total_yields += 1
|
||||
|
||||
return total_yields
|
||||
|
||||
|
||||
# Funkcja do generowania planszy/ogrodu i zapisywania go jako lista z liczbą plonów
|
||||
def generate_garden_with_yields(rows=NUM_Y, cols=NUM_X):
|
||||
garden = generate_garden(rows, cols)
|
||||
total_yields = calculate_yields(garden)
|
||||
return [garden, total_yields]
|
||||
|
||||
|
||||
# Funkcja do generowania linii cięcia i zapisywania jej jako liczba roślin w kolumnie z pierwszej planszy/ogrodu
|
||||
def line():
|
||||
path = []
|
||||
flag = False
|
||||
x = random.randint(4, 8)
|
||||
position = (0, x)
|
||||
path.append(position)
|
||||
while not flag: # wybór punktu dopóki nie wybierze się skrajnego
|
||||
# prawdopodobieństwo "ruchu" -> 0.6: w prawo, 0.2: w góre, 0.2: w dół
|
||||
p = [(position[0] + 1, position[1]), (position[0], position[1] + 1), (position[0], position[1] - 1)]
|
||||
w = [0.6, 0.2, 0.2]
|
||||
position2 = random.choices(p, w)[0]
|
||||
if position2 not in path: # sprawdzenie czy dany punkt nie był już wybrany aby nie zapętlać się
|
||||
path.append(position2)
|
||||
position = position2
|
||||
if position[0] == NUM_X or position[1] == 0 or position[1] == NUM_Y: # sprawdzenie czy osiągnięto skrajny punkt
|
||||
flag = True
|
||||
info = [] # przeformatowanie sposobu zapisu na liczbę roślin w kolumnie, które będzię się dzidziczyło z pierwszej planszy/ogrodu
|
||||
for i in range(len(path) - 1):
|
||||
if path[i + 1][0] - path[i][0] == 1:
|
||||
info.append(NUM_Y - path[i][1])
|
||||
if len(info) < NUM_X: # uzupełnienie informacji o dziedziczeniu z planszy/ogrodu
|
||||
if path[-1:][0][1] == 0:
|
||||
x = NUM_Y
|
||||
else:
|
||||
x = 0
|
||||
while len(info) < NUM_X:
|
||||
info.append(x)
|
||||
# return path, info
|
||||
return info
|
||||
|
||||
|
||||
# Funkcja do generowania potomstwa
|
||||
def divide_gardens(garden1, garden2):
|
||||
info = line()
|
||||
new_garden1 = [[] for _ in range(NUM_Y)]
|
||||
new_garden2 = [[] for _ in range(NUM_Y)]
|
||||
for i in range(NUM_X):
|
||||
for j in range(NUM_Y):
|
||||
# do utworzonych kolumn w nowych planszach/ogrodach dodajemy dziedziczone rośliny
|
||||
if j < info[i]:
|
||||
new_garden1[j].append(garden1[j][i])
|
||||
new_garden2[j].append(garden2[j][i])
|
||||
else:
|
||||
new_garden1[j].append(garden2[j][i])
|
||||
new_garden2[j].append(garden1[j][i])
|
||||
|
||||
return [new_garden1, calculate_yields(new_garden1)], [new_garden2, calculate_yields(new_garden2)]
|
||||
|
||||
|
||||
# Funkcja do mutacji danej planszy/ogrodu
|
||||
def mutation(garden, not_used):
|
||||
new_garden = copy.deepcopy(garden)
|
||||
for i in range(NUM_X):
|
||||
x = random.randint(0, 11) # wybieramy, w którym wierszu w i-tej kolumnie zmieniamy roślinę na inną
|
||||
other_plants = [plant for plant in plants if plant != new_garden[x][i]]
|
||||
new_garden[x][i] = random.choice(other_plants)
|
||||
return [new_garden, calculate_yields(new_garden)]
|
||||
|
||||
|
||||
# Funkcja do generowania pierwszego pokolenia
|
||||
def generate(n):
|
||||
generation = []
|
||||
for i in range(n * 3):
|
||||
generation.append(generate_garden_with_yields())
|
||||
generation.sort(reverse=True, key=lambda x: x[1])
|
||||
return generation[:n]
|
||||
|
||||
|
||||
# Funkcja do implementacji ruletki (sposobu wyboru) - sumuje wszystkie plony generacji
|
||||
def sum_yields(x):
|
||||
s = 0
|
||||
for i in range(len(x)):
|
||||
s += x[i][1]
|
||||
return s
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
roulette = True
|
||||
attemps = 1
|
||||
population = 120
|
||||
best = []
|
||||
iter = 0
|
||||
for a in range(attemps):
|
||||
generation = generate(population)
|
||||
print(generation[0][1])
|
||||
while generation[0][1] != NUM_X*NUM_Y: # ile iteracji - nowych pokoleń
|
||||
iter += 1
|
||||
print(iter)
|
||||
print(generation[0][1])
|
||||
new_generation = generation[:(population // 7)] # dziedziczenie x najlepszych osobników
|
||||
j = 0
|
||||
while j < (
|
||||
population - (
|
||||
population // 7)): # dobór reszty osobników do pełnej liczby populacji danego pokolenia
|
||||
if roulette: # zasada ruletki -> "2 rzuty kulką"
|
||||
s = sum_yields(generation) # suma wszystkich plnów całego pokolenia
|
||||
z = []
|
||||
if s == 0: # wtedy każdy osobnik ma takie same szanse
|
||||
z.append(random.randint(0, population - 1))
|
||||
z.append(random.randint(0, population - 1))
|
||||
else:
|
||||
weights = [] # wagi prawdopodobieństwa dla każdego osobnika generacji
|
||||
pos = [] # numery od 0 do 49 odpowiadające numerom osobnikom w generacji
|
||||
for i in range(population):
|
||||
weights.append(generation[i][1] / s)
|
||||
pos.append(i)
|
||||
z.append(random.choices(pos, weights)[0]) # wybranie osobnika według wag prawdopodobieństwa
|
||||
z.append(random.choices(pos, weights)[0]) # wybranie osobnika według wag prawdopodobieństwa
|
||||
else: # metoda rankingu
|
||||
z = random.sample(range(0, int(population // 1.7)), 2)
|
||||
|
||||
# krzyzowanie 90% szans, mutacja 10% szans
|
||||
function = [divide_gardens, mutation]
|
||||
weight = [0.9, 0.1]
|
||||
fun = random.choices(function, weight)[0]
|
||||
h = fun(generation[z[0]][0], generation[z[1]][0])
|
||||
if len(h[0]) == 2:
|
||||
new_generation.append(h[0])
|
||||
new_generation.append(h[1])
|
||||
j += 2
|
||||
else:
|
||||
new_generation.append(h)
|
||||
j += 1
|
||||
|
||||
new_generation.sort(reverse=True, key=lambda x: x[1]) # sortowanie malejąco listy według wartości plonów
|
||||
generation = new_generation[:population]
|
||||
|
||||
best.append(generation[0])
|
||||
|
||||
best.sort(reverse=True, key=lambda x: x[1])
|
||||
|
||||
# Zapis do pliku
|
||||
# for i in range(len(best)):
|
||||
# print(best[i][1], calculate_yields(best[i][0]))
|
||||
#
|
||||
#
|
||||
# with open(f'pole3_pop{population}_{iter}_{roulette}.json', 'w') as file: # zapis planszy/ogrodu do pliku json
|
||||
# json.dump(best[0][0], file, indent=4)
|
||||
#
|
||||
# print("Dane zapisane do pliku")
|
||||
#
|
||||
# Odczyt z pliku
|
||||
# with open(f'pole3_pop{population}_{iter}_{roulette}.json', 'r') as file:
|
||||
# garden_data = json.load(file)
|
||||
#
|
||||
# print("Odczytane dane ogrodu:")
|
||||
# for row in garden_data:
|
||||
# print(row)
|
||||
#
|
||||
# print(calculate_yields(garden_data))
|
||||
# if best[0][0] == garden_data:
|
||||
# print("POPRAWNE: ", calculate_yields(garden_data), calculate_yields(best[0][0]))
|
||||
266
pole2_pop120_iter2500_True.json
Normal file
266
pole2_pop120_iter2500_True.json
Normal file
@ -0,0 +1,266 @@
|
||||
[
|
||||
[
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"tomato",
|
||||
"corn",
|
||||
"carrot",
|
||||
"potato",
|
||||
"potato",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato"
|
||||
],
|
||||
[
|
||||
"corn",
|
||||
"carrot",
|
||||
"potato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"potato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"potato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"carrot",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn"
|
||||
],
|
||||
[
|
||||
"carrot",
|
||||
"potato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"corn",
|
||||
"carrot",
|
||||
"potato",
|
||||
"carrot",
|
||||
"potato",
|
||||
"carrot",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato"
|
||||
],
|
||||
[
|
||||
"potato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"carrot",
|
||||
"corn",
|
||||
"carrot",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn"
|
||||
],
|
||||
[
|
||||
"potato",
|
||||
"carrot",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato"
|
||||
],
|
||||
[
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn"
|
||||
],
|
||||
[
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato"
|
||||
],
|
||||
[
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn"
|
||||
],
|
||||
[
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"carrot",
|
||||
"corn",
|
||||
"tomato"
|
||||
],
|
||||
[
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"carrot",
|
||||
"potato",
|
||||
"tomato",
|
||||
"potato"
|
||||
],
|
||||
[
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"carrot",
|
||||
"corn",
|
||||
"carrot",
|
||||
"corn",
|
||||
"carrot",
|
||||
"potato",
|
||||
"potato",
|
||||
"tomato",
|
||||
"potato"
|
||||
],
|
||||
[
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"potato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"corn",
|
||||
"tomato"
|
||||
]
|
||||
]
|
||||
266
pole3_pop120_365_True.json
Normal file
266
pole3_pop120_365_True.json
Normal file
@ -0,0 +1,266 @@
|
||||
[
|
||||
[
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato",
|
||||
"tomato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"potato",
|
||||
"carrot",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato",
|
||||
"potato",
|
||||
"potato",
|
||||
"carrot"
|
||||
],
|
||||
[
|
||||
"tomato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"potato",
|
||||
"tomato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"potato"
|
||||
],
|
||||
[
|
||||
"corn",
|
||||
"carrot",
|
||||
"corn",
|
||||
"carrot",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"carrot",
|
||||
"potato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"corn",
|
||||
"carrot",
|
||||
"potato",
|
||||
"potato",
|
||||
"tomato"
|
||||
],
|
||||
[
|
||||
"tomato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"corn",
|
||||
"tomato",
|
||||
"corn",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"corn",
|
||||
"carrot",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"corn",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato",
|
||||
"potato",
|
||||
"tomato",
|
||||
"tomato"
|
||||
],
|
||||
[
|
||||
"tomato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"corn",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato",
|
||||
"tomato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato",
|
||||
"tomato",
|
||||
"tomato",
|
||||
"potato",
|
||||
"potato"
|
||||
],
|
||||
[
|
||||
"potato",
|
||||
"tomato",
|
||||
"potato",
|
||||
"potato",
|
||||
"tomato",
|
||||
"corn",
|
||||
"carrot",
|
||||
"potato",
|
||||
"potato",
|
||||
"tomato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato",
|
||||
"carrot",
|
||||
"potato",
|
||||
"tomato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot"
|
||||
],
|
||||
[
|
||||
"potato",
|
||||
"potato",
|
||||
"tomato",
|
||||
"tomato",
|
||||
"corn",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato",
|
||||
"tomato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato"
|
||||
],
|
||||
[
|
||||
"carrot",
|
||||
"potato",
|
||||
"tomato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato",
|
||||
"potato",
|
||||
"tomato",
|
||||
"tomato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"potato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato",
|
||||
"carrot",
|
||||
"corn",
|
||||
"carrot"
|
||||
],
|
||||
[
|
||||
"carrot",
|
||||
"potato",
|
||||
"tomato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato",
|
||||
"tomato",
|
||||
"potato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato",
|
||||
"tomato",
|
||||
"corn"
|
||||
],
|
||||
[
|
||||
"potato",
|
||||
"tomato",
|
||||
"tomato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"potato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"potato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato",
|
||||
"carrot",
|
||||
"corn",
|
||||
"tomato",
|
||||
"potato",
|
||||
"tomato"
|
||||
],
|
||||
[
|
||||
"potato",
|
||||
"tomato",
|
||||
"corn",
|
||||
"tomato",
|
||||
"potato",
|
||||
"potato",
|
||||
"potato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"corn",
|
||||
"tomato",
|
||||
"potato"
|
||||
],
|
||||
[
|
||||
"potato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"corn",
|
||||
"carrot",
|
||||
"potato",
|
||||
"potato",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato",
|
||||
"carrot",
|
||||
"carrot",
|
||||
"potato",
|
||||
"carrot",
|
||||
"corn",
|
||||
"carrot",
|
||||
"corn",
|
||||
"tomato"
|
||||
]
|
||||
]
|
||||
@ -7,7 +7,7 @@ Required packages:
|
||||
pip install pandas
|
||||
How to run:
|
||||
For BFS3:
|
||||
-in App.py change bfs3_flag to True (other flags need to be disabled)
|
||||
-in App.py: -change bfs3_flag to True (other flags need to be disabled) -ensure that in App.py in BFS3 you give goalTreasure
|
||||
-in Image.py change range in function return_random_plant to (0,5)
|
||||
For Astar:
|
||||
in App.py change Astar to True (other flags need to be disabled)
|
||||
|
||||
Loading…
Reference in New Issue
Block a user