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algorithm_algorithm.txt
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algorithm_algorithm.txt
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def initialize_algorithm():
initial_solution = "Initial Solution"
language_model = "GPT-4" # Example
utility_function = define_utility_function() # User-defined
return initial_solution, language_model, utility_function
def iterative_improvement(initial_solution, language_model, utility_function):
n_iterations = 5
best_solution = initial_solution
for i in range(n_iterations):
try:
improved_solution = improve_solution(best_solution, language_model, utility_function)
if utility_function(improved_solution) > utility_function(best_solution):
best_solution = improved_solution
except Exception as e:
log_error(e)
finally:
optimize_memory()
return best_solution
def generate_parallel_solutions(language_model, n_solutions):
with ThreadPoolExecutor(max_workers=n_solutions) as executor:
futures = [executor.submit(generate_solution, language_model) for _ in range(n_solutions)]
return [future.result() for future in futures]
def integrate_user_feedback(solution, feedback):
# Modify the solution based on user feedback
return modified_solution
def utility_function(solution):
# Assess the solution's quality
return score
def adjust_temperature(iteration, max_iterations):
# Adjust temperature based on progress
return new_temperature