Skip to content

😴 Habituation — Anti-Filter Bubble

Package: com.spectrayan.spector.memory.habituation

Biological Analog: Habituation is the simplest form of learning — a decrease in response to a stimulus after repeated presentations. You stop hearing the ticking clock after a few minutes. The brain allocates attention to novel stimuli, not repeated ones. This prevents sensory overload and enables adaptation.

The Problem

Without habituation, an AI agent repeatedly recalls the same "most relevant" memories — creating a filter bubble. If memory A has the highest similarity score, it dominates every recall, crowding out potentially useful but slightly-less-similar memories.

Query 1: "database issues" → [A, B, C, D, E]     ← A dominates
Query 2: "database issues" → [A, B, C, D, E]     ← Same results!
Query 3: "database issues" → [A, B, C, D, E]     ← Filter bubble

With Habituation

Query 1: "database issues" → [A, B, C, D, E]     ← Fresh results
Query 2: "database issues" → [B, C, A, D, F]     ← A drops, F emerges
Query 3: "database issues" → [C, F, B, G, D]     ← New memories surface

HabituationPenalty

The HabituationPenalty tracks recall frequency per memory ID and computes a decay penalty:

public final class HabituationPenalty {

    private final ConcurrentHashMap<String, Integer> recallCounts 
        = new ConcurrentHashMap<>();
    private final float decayRate;  // default: 0.85

    /**
     * Records a recall event and returns the habituation penalty.
     * First recall: 1.0 (no penalty). Each subsequent recall multiplies
     * the penalty by decayRate (default: 0.85).
     *
     * @param memoryId the memory being recalled
     * @return penalty multiplier [0.0 – 1.0]
     */
    public float recordAndComputePenalty(String memoryId) {
        int count = recallCounts.merge(memoryId, 1, Integer::sum);
        if (count <= 1) return 1.0f;  // First recall — no penalty
        return (float) Math.pow(decayRate, count - 1);
    }

    /**
     * Batch penalty computation for multiple IDs (P7 optimization).
     */
    public float[] batchPenalty(String[] ids) {
        float[] penalties = new float[ids.length];
        for (int i = 0; i < ids.length; i++) {
            penalties[i] = recordAndComputePenalty(ids[i]);
        }
        return penalties;
    }
}

Penalty Curve

Recall # Penalty (rate=0.85) Effect
1st 1.00 Full score
2nd 0.85 15% reduction
3rd 0.72 28% reduction
5th 0.52 Half score
10th 0.20 80% reduction
20th 0.04 Nearly eliminated

Decay Rate Configuration

The default decay rate of 0.85 provides a balance between novelty and relevance. A higher rate (0.95) creates a gentler penalty — useful when the agent genuinely needs to recall the same memory frequently. A lower rate (0.70) aggressively surfaces new content.

Integration with RecallPipeline

Habituation is applied at Step 5 of the recall pipeline — after scoring but before final ranking:

// In RecallPipeline.recall()

// Step 5: Apply habituation penalty (anti-filter-bubble)
for (int i = 0; i < allResults.size(); i++) {
    CognitiveResult r = allResults.get(i);
    float habPenalty = habituationPenalty.recordAndComputePenalty(r.id());
    if (habPenalty < 1.0f) {
        allResults.set(i, new CognitiveResult(
            r.id(), r.text(), r.score() * habPenalty, 
            r.importance(), r.ageDays(),
            r.recallCount(), r.valence(), r.memoryType(), r.source(),
            r.synapticTags(), r.decayFactor(), r.ltpAdjustedDecay()));
    }
}

Key: The penalty multiplies the score() field — it doesn't modify the underlying memory. Habituation is a recall-time effect, not a storage-time effect.

Interaction with Other Systems

System Interaction
Reconsolidation Habituation reduces recall score, but reconsolidation increases the memory's durability. A frequently-recalled memory resists temporal decay (fewer buckets) but gets a lower score on repeated queries.
Surprise Detection New, surprising memories start with high importance and no habituation penalty — they naturally dominate initial queries.
Suppression If a memory is fully suppressed, habituation is irrelevant — it's excluded at Step 4 before habituation is applied.

Next Steps