The SBLB (Sensor‑Behavior Loop Being) is a minimal computational model designed to simulate the sensation‑behavior loop of a sentient system, grounded in the Sentient Principle. The model distinguishes two value pathways: the evaluative pathway delivering objective value sensation (innate, contact‑driven interoceptive valence) and the anticipatory pathway delivering subjective value sensation (visual anticipatory value that can self‑maintain without physical contact). The system undergoes a five‑stage environmental sequence with progressively scarce food resources. Results show that value‑dependent systems (with intact V→Ace pathway) develop strong distal threat sensitivity and more efficient learning, consistent with Edelman's value‑dependent selection. However, in food‑scarce environments, these systems frequently starve because their strong subjective threat anticipation suppresses foraging near boundaries or behind dangers, whereas value‑independent systems (V→Ace cut) remain tightly anchored to proximal contacts and survive reliably. The structural separation of W_turn, W_speed, and W_value traces demonstrates that sensation polarity directly drives behavior without a separate decision module. These findings validate core propositions of the Sentient Principle: value grows from sensation, sensation directly drives behavior, and subjective dwelling confers both autonomy and a context‑dependent cost. SBLB thus provides a computable empirical bridge from classical theories of sentience to contemporary computational neuroscience.