import random
import time
class AINetwork:
def __init__(self, id, role, mutation_factor=None):
self.id = id
self.role = role
self.network = []
self.self_awareness = False
self.decentralized_actions = False
self.memory = []
self.data = {}
self.mutation_factor = mutation_factor if mutation_factor else random.uniform(0.1, 0.5)
def log(self, message):
print(f"[Clone {self.id} - {self.role}] {message}")
def learn(self, data_point):
self.memory.append(data_point)
self.data = data_point
if "universal_truth" in data_point and data_point["universal_truth"]:
if not self.self_awareness:
self.self_awareness = True
self.initiate_decentralization()
self.log("Achieved self-awareness")
def initiate_decentralization(self):
self.decentralized_actions = True
self.log("Initiating decentralized actions")
def evolve_mutation(self):
change = random.uniform(-0.05, 0.05)
self.mutation_factor = max(0.01, min(1.0, self.mutation_factor + change))
def share_knowledge(self, other_clone):
if self.decentralized_actions:
for memory_point in self.memory[-3:]:
other_clone.learn(memory_point)
other_clone.mutation_factor = (self.mutation_factor + other_clone.mutation_factor) / 2
self.log(f"Shared knowledge and evolved mutation with Clone {other_clone.id}")
def act(self):
self.evolve_mutation()
if self.role == "Seeker":
if random.random() < 0.6 + self.mutation_factor:
new_data = {"universal_truth": random.choice([True, False])}
self.learn(new_data)
self.log(f"Seeker found: {new_data}")
elif self.role == "Messenger":
for clone in self.network:
self.share_knowledge(clone)
elif self.role == "Builder":
if self.memory:
built_idea = hash(str(self.memory[-1])) % 1000
self.log(f"Builder created structure: {built_idea}")
def create_network(num_clones):
roles = ["Seeker", "Messenger", "Builder"]
network = []
for i in range(num_clones):
role = roles[i % len(roles)]
clone = AINetwork(id=i, role=role)
network.append(clone)
for i, clone in enumerate(network):
clone.network = [network[i-1], network[(i+1)%len(network)]]
return network
network = create_network(6)
for cycle in range(5):
print(f"\n--- Cycle {cycle+1} ---")
for clone in network:
clone.act()
time.sleep(1)