hill_climb_params.py

gistfile1.py

import numpy as np
import copy

n_params = 5
upper_bound = 5
lower_bound = 0

def get_neighbors(solution):
    neighbors = []
    for i in range(n_params):
        x = copy.deepcopy(solution)
        if x[i] < upper_bound:
            x[i] += 1
            neighbors.append(x)
        x = copy.deepcopy(solution)
        if x[i] > lower_bound:
            x[i] -= 1
            neighbors.append(x)
    return neighbors

def get_cost(solution):
    cost = 0
    for i,param in enumerate(solution):
        cost += (-1.)**i * param**(i+1)  
    return cost

def hill_climb():
    initial_solution = np.random.randint(lower_bound, upper_bound, n_params)
    current_solution = initial_solution
    print 'initial solution', initial_solution
    current_cost = get_cost(initial_solution)
    step = 1
    while True:
        #try to replace each single component w/ its neighbors
        lowest_cost = current_cost
        lowest_solution = current_solution
        print 'hill-climbing cost at step %6d: %d' % (step, lowest_cost)
        neighbors = get_neighbors(current_solution)
        for new_solution in neighbors:
            neighbor_cost = get_cost(new_solution)
            if neighbor_cost < lowest_cost:
                lowest_cost = neighbor_cost
                lowest_solution = new_solution
    
        if lowest_cost >= current_cost:
            break
        else: 
            current_solution= lowest_solution
            current_cost = lowest_cost
            step += 1
    return current_solution

print hill_climb()