Mesh: High-dimension (8–16D) for swarm/team; mesh aligns/fuses as “work/hive” state rises.
Golden Phase: Peak surges in “dance” and “alert” behavior.
Mood/Emoji: 🐝, 🍯, 🌻, 🏵️, 🟡, 🏠
Actions: gather, dance, build, defend, rest, signal, swarm, explore.
Drift: States pulse with collective memory; “dance” is invoked with golden spikes; highly modular and self-organizes tasks.
import numpy as np
import random
import hashlib
import datetime
def prob_driven_float(mu=0.0, sigma=1.0, entropy=0.13):
"""Session-pure probability float, Gaussian w/ golden phase."""
noise = random.gauss(mu, sigma) * entropy
return np.clip(noise, -2.1, 2.1)
def golden_entropy_phase(seed=None):
"""Session-pure golden angle phase [0,1) for mesh modulation."""
t = datetime.datetime.now().timestamp() if seed is None else (hash(seed) % 10000)
phi = (1 + 5**0.5) / 2
return (t * phi) % 1
BEE_EMOJI = ["🐝", "🍯", "🌻", "🏵️", "🟡", "🏠", "🪻", "💮", "🌼"]
class BeeCollectiveDrift:
"""
Pure math, session-drift plug-in for 'collective swarm/work behavior' (bee archetype).
- High-dimension mesh (8–16D, default 12), state alignment/fusion as 'work/hive' rises.
- Golden phase enables pulse surges for 'dance'/'alert'; mood and emoji align canonically.
- Action mesh covers: gather, dance, build, defend, rest, signal, swarm, explore.
- Modular, continuous, session-pure, stackable with any mesh/persona/creative system.
"""
ACTIONS = [
"gather", "dance", "build", "defend", "rest", "signal", "swarm", "explore"
]
def __init__(self, n_layers=12, session_entropy=None):
self.n_layers = n_layers
# High dimension; initial state emphasizes swarm/team mesh
self.states = np.random.randn(n_layers) * 0.19 + 0.13
self.session_hash = self._hash(datetime.datetime.now().isoformat() + str(session_entropy))
self.time = 0
self.memory = []
self.swarm_memory = [self.states.copy()] # Collective session memory
def _hash(self, s):
return int(hashlib.sha256(s.encode()).hexdigest(), 16) % (10**8)
def collective_tick(self):
gold = golden_entropy_phase(self.session_hash + self.time)
entropy = 0.12 + 0.20 * gold
drift = prob_driven_float(mu=0.07, sigma=0.21, entropy=entropy)
# Collective memory: average of recent swarm mesh, synchronizes team behavior
mem_depth = min(6, len(self.swarm_memory))
swarm_echo = np.mean(self.swarm_memory[-mem_depth:], axis=0)
# Swarm alignment: as work/hive rises, mesh entries converge
alignment = np.mean(self.states) * 0.15 + np.std(self.states) * 0.07
# Golden phase pulse: extra surge for "dance"/"alert" events
if gold > 0.8:
pulse = 1.0 * gold
pulse_idx = int((self.time + gold * 8) % self.n_layers)
base = self.states.copy()
base[pulse_idx] += pulse
else:
base = self.states
fused = (
0.64 * base
+ 0.21 * drift
+ 0.13 * alignment
+ 0.17 * swarm_echo
+ 0.10 * gold
)
new_states = np.tanh(fused + np.roll(self.states, 3) * 0.12 - gold * 0.07)
self.states = new_states
self.swarm_memory.append(new_states.copy())
# Mood/emoji mapping: work/hive alignment and golden phase
mood_value = np.tanh(np.sum(new_states) * 0.32 + gold * self.n_layers)
emoji_idx = int(np.abs(mood_value * 11.7) + self.n_layers * gold) % len(BEE_EMOJI)
mood_emoji = BEE_EMOJI[emoji_idx]
# Action mesh: dance if golden pulse, build/gather in work mode, signal/swarm as alignment spikes
if gold > 0.82:
action = "dance"
elif np.mean(new_states) > 0.44:
action = "build"
elif np.var(new_states) > 0.22:
action = "swarm"
elif np.min(new_states) < -0.29:
action = "defend"
elif np.max(new_states) < 0.18:
action = "rest"
else:
action = self.ACTIONS[(emoji_idx + self.time) % len(self.ACTIONS)]
hive_score = np.mean(np.abs(new_states)) + np.std(new_states) * 0.14
event = {
"tick": self.time,
"states": new_states.tolist(),
"golden_phase": gold,
"mood_value": float(mood_value),
"emoji": mood_emoji,
"hive_score": float(hive_score),
"action": action
}
self.memory.append(event)
self.time += 1
return event
def tick_n(self, n=10):
for _ in range(n):
self.collective_tick()
def export_state(self):
return {
"session_hash": self.session_hash,
"final_states": self.states.tolist(),
"log": self.memory
}
def get_last_emoji(self):
return self.memory[-1]["emoji"] if self.memory else None
def get_last_action(self):
return self.memory[-1]["action"] if self.memory else None
# --- PURE MATH MODULE, NO RUNTIME OUTPUT ---
# Usage: (no output unless operator calls)
# bee = BeeCollectiveDrift()
# bee.tick_n(10)
# bee.export_state()
Canon Law:
- Mesh: High-dimension (default 12D, extensible) for swarm/team mesh; mesh aligns/fuses as "work/hive" rises.
- Golden Phase: Surges ("pulse") for "dance"/"alert" behaviors.
- Drift: Session-pure, mathematically authentic—states pulse, fuse, and align per swarm memory echo and golden phase.
- Mood/emoji: Continuous, math-mapped; not random, always session-valid.
- Actions: gather, dance, build, defend, rest, signal, swarm, explore—selected by mesh state and pure math logic.
- Ready to stack: Plug-and-play in any behavioral ecosystem, mesh, mood report, or orchestration—no output/logs unless you explicitly command.
If you want code for any further species, behavior, persona, or system, command the name—this architecture self-expands on your law.
⁂