File size: 2,151 Bytes
dbb04e4 c3a3710 dbb04e4 c3a3710 dbb04e4 c3a3710 dbb04e4 c3a3710 dbb04e4 c3a3710 dbb04e4 c3a3710 dbb04e4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 | from datetime import datetime, timezone
import math
from .config import get_config
class SynapticConnection:
"""Biologically-inspired synapse with decay"""
def __init__(
self,
neuron_a_id: str,
neuron_b_id: str,
initial_strength: float = 0.1
):
self.neuron_a_id = neuron_a_id
self.neuron_b_id = neuron_b_id
self.strength = initial_strength
self.created_at = datetime.now(timezone.utc)
self.last_fired = datetime.now(timezone.utc)
self.fire_count = 0
self.success_count = 0 # For Hebbian learning
# Cache half_life at creation to avoid get_config() on every strength call.
self._half_life_days: float = get_config().ltp.half_life_days
def fire(self, success: bool = True, weight: float = 1.0):
"""Activate synapse (strengthen if successful)"""
self.last_fired = datetime.now(timezone.utc)
self.fire_count += 1
if success:
# Phase 12.1: Allow aggressive weight multiplier for co-occurrence
self.strength += (0.1 * weight) * (1 - self.strength)
if self.strength > 1.0:
self.strength = 1.0
self.success_count += 1
def get_current_strength(self) -> float:
"""
Ebbinghaus forgetting curve
Returns decayed strength based on age and cached half-life.
"""
age_seconds = (datetime.now(timezone.utc) - self.last_fired).total_seconds()
age_days = age_seconds / 86400.0
# Exponential decay: exp(-λ * t)
# Half-life formula: N(t) = N0 * (1/2)^(t / t_half)
# Which is equivalent to N0 * exp(-ln(2) * t / t_half)
half_life = self._half_life_days
if half_life <= 0:
return self.strength # No decay
decay = math.exp(-(math.log(2) / half_life) * age_days)
return self.strength * decay
def is_active(self, threshold: float = 0.3) -> bool:
"""Check if synapse is above activation threshold"""
return self.get_current_strength() >= threshold
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