import deap #import NN from walker_NN import NNN from deap import base from deap import creator from deap import tools import math import gym import random from gym import wrappers import time import numpy as np from deap import algorithms nn = NNN() env = gym.make("BipedalWalker-v2") MAX_STEPS = 3700 w_list = [] def forward(network, X): def sigmoid(x): return 1 / (1 + np.exp(-x)) W1, W2, W3 = network['W1'], network['W2'], network['W3'] b1, b2, b3 = network['B1'], network['B2'], network['B3'] a1 = np.dot(X, W1) + b1 a1 = np.dot(X, W1) + b1 z1 = a1 a2 = np.dot(z1, W2) + b2
from walker_NN import NNN from deap import base from deap import creator from deap import tools import math import gym import random from gym import wrappers import time import numpy as np from deap import algorithms import pickle NGEN = 300 env = gym.make("BipedalWalker-v2") nn = NNN() POPNUM = 250 MAX_STEPS = 3700 w_list = [] # In[9]: count = 0 CXPB = 0.5 MUTPB = 0.1 creator.create( "FitnessMax", base.Fitness, weights=[1.0], ) creator.create("Individual", list, fitness=creator.FitnessMax) toolbox = base.Toolbox()