ai_lab_8

import random
def objective_function(x):
return -x**2 + 10*x + 25
def hill_climbing(max_iterations=1000, step_size=0.1):
current_solution = random.uniform(-10, 10)
current_value = objective_function(current_solution)
for _ in range(max_iterations):
neighbor_solution = current_solution + random.uniform(-step_size,
step_size)
neighbor_value = objective_function(neighbor_solution)
if neighbor_value > current_value:
current_solution = neighbor_solution
current_value = neighbor_value
return current_solution, current_value
if name == "main":
best_solution, best_value = hill_climbing()
print("Best solution:", best_solution)
print("Best value:", best_value)