Added random seed
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31
src/AI/GA.py
31
src/AI/GA.py
@ -39,8 +39,13 @@ def geneticAlgorithm(map, iter, solutions, mutationAmount=0.05, multithread=Fals
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f.write("GA Results from " + str(datetime.now()))
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f.write("\n")
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# Set the RNG seed for this GA
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random.seed(random.randint(0, 100))
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# Begin
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for i in range(iter):
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print("\nRunning {} generation...".format(i + 1))
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fitness = []
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if not multithread:
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for player in population:
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@ -172,23 +177,20 @@ def pickEntity(player, map):
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foodsWeights = []
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hunger = player.statistics.hunger
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for food in foods:
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distance = abs(player.x - food.x) + abs(player.y - food.y)
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typeWeight = weights[0]
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foodsWeights.append((typeWeight * (walkingAffinity / distance)) * hunger)
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foodsWeights.append(typeWeight * hunger)
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watersWeights = []
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thirst = player.statistics.thirst
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for water in waters:
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distance = abs(player.x - water.x) + abs(player.y - water.y)
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typeWeight = weights[1]
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watersWeights.append((typeWeight * (walkingAffinity / distance)) * thirst)
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watersWeights.append(typeWeight * thirst)
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restsWeights = []
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stamina = player.statistics.stamina
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for rest in rests:
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distance = abs(player.x - rest.x) + abs(player.y - rest.y)
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typeWeight = weights[2]
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restsWeights.append((typeWeight * (walkingAffinity / distance)) / stamina)
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restsWeights.append(typeWeight * stamina)
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finalEntities = foods + waters + rests
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finalWeights = foodsWeights + watersWeights + restsWeights
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@ -196,6 +198,19 @@ def pickEntity(player, map):
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if not finalEntities:
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# If all items are gone, pick random one
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finalEntities = map.getInteractablesByClassifier()
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rng = random.Random()
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choice = rng.choices(finalEntities, finalWeights)[0]
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# Pick best weighted entities
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bestIdxs = (numpy.where(finalWeights == numpy.max(finalWeights)))[0]
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bestEntities = []
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for i in bestIdxs:
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bestEntities.append(finalEntities[i])
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choice = random.choice(bestEntities)
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# Keeps the player from standing still
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if choice == map.getEntityOnCoord(player.getFacingCoord()):
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choice = random.choice(finalEntities)
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# Old method using RNG
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# choice = random.choices(finalEntities, finalWeights)[0]
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return choice
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