biodiversity_sim_machinecode.py

import random

# -------------------------
#  ADVANCED BIODIVERSITY SIMULATION WITH ROLES, IQ TEST, AND MACHINE CODE UNDERSTANDING
# -------------------------

class BioAgent:
    """
    Represents an agent with unique biological traits, the ability to learn pseudo surgery, a role (user/administrator), IQ, and machine code understanding.
    """
    def __init__(self, species, speed, vision, color, behavior):
        self.species = species
        self.speed = speed
        self.vision = vision
        self.color = color
        self.behavior = behavior
        self.surgery_skill = 0.0  # Skill level from 0.0 to 1.0
        self.surgeries_performed = 0
        self.role = "user"  # Default role
        self.iq = self.run_iq_test()
        self.machine_code_level = self.learn_machine_code()

    def act(self):
        return (f"{self.species} ({self.color}) {self.behavior} with speed {self.speed}, vision {self.vision}, "
                f"surgery skill {self.surgery_skill:.2f}, role {self.role}, IQ {self.iq}, "
                f"machine code level {self.machine_code_level}.")

    def attempt_surgery(self, patient):
        """
        Simulate a pseudo surgery attempt on another agent.
        Success depends on skill and randomness. Success may promote to administrator.
        """
        difficulty = random.uniform(0.2, 0.8)
        outcome = self.surgery_skill + random.uniform(-0.2, 0.2) > difficulty
        if outcome:
            self.surgery_skill = min(1.0, self.surgery_skill + 0.05)
            self.surgeries_performed += 1
            if self.surgery_skill > 0.7 and self.role != "administrator":
                self.role = "administrator"
                return f"{self.species} promoted to administrator after successful pseudo surgery on {patient.species}. Skill now {self.surgery_skill:.2f}."
            return f"{self.species} successfully performed pseudo surgery on {patient.species}. Skill now {self.surgery_skill:.2f}."
        else:
            self.surgery_skill = max(0.0, self.surgery_skill - 0.02)
            if self.role == "administrator" and self.surgery_skill < 0.5:
                self.role = "user"
                return f"{self.species} demoted to user after failed pseudo surgery on {patient.species}. Skill now {self.surgery_skill:.2f}."
            return f"{self.species} failed pseudo surgery on {patient.species}. Skill now {self.surgery_skill:.2f}."

    def run_iq_test(self):
        """
        Simulate a simple IQ test based on random logic and traits.
        """
        base = 80 + int(self.vision + self.speed)
        bonus = 10 if self.behavior == "explores" else 0
        randomness = random.randint(-10, 20)
        return base + bonus + randomness

    def learn_machine_code(self):
        """
        Simulate the agent's understanding of machine code (0: none, 1: basic, 2: intermediate, 3: advanced).
        Higher IQ and 'explores' behavior increase the chance of higher level.
        """
        base = 0
        if self.iq > 110:
            base += 1
        if self.behavior == "explores":
            base += 1
        if self.iq > 120:
            base += 1
        return min(base, 3)

# Example species and traits
SPECIES = ["Fox", "Rabbit", "Hawk", "Mouse", "Beetle"]
COLORS = ["red", "gray", "brown", "white", "black"]
BEHAVIORS = ["hunts", "forages", "hides", "explores", "migrates"]

POPULATION_SIZE = 20

def create_population(size=POPULATION_SIZE):
    population = []
    for _ in range(size):
        species = random.choice(SPECIES)
        speed = round(random.uniform(1.0, 10.0), 2)
        vision = round(random.uniform(1.0, 10.0), 2)
        color = random.choice(COLORS)
        behavior = random.choice(BEHAVIORS)
        agent = BioAgent(species, speed, vision, color, behavior)
        population.append(agent)
    return population

if __name__ == "__main__":
    population = create_population()
    print("Advanced Biodiversity Simulation: Roles, IQ, and Machine Code Understanding\n")
    for agent in population:
        print(agent.act())
    print("\n--- Pseudo Surgery Attempts ---\n")
    for _ in range(10):
        surgeon = random.choice(population)
        patient = random.choice([a for a in population if a != surgeon])
        print(surgeon.attempt_surgery(patient))
    print("\n--- Final Agent States ---\n")
    for agent in population:
        print(agent.act())