# 4.4 Emotional Curve

The Emotional Curve models how a pet’s internal state evolves in response to time, interaction, and environmental triggers. While Behavior Weights define what a pet tends to do, the Emotional Curve governs how it feels and how those feelings change. This concept is inspired by affective computing but adapted to a persistent, owner-centric digital companion. Each pet maintains a set of emotional axes—such as comfort, excitement, attachment, or focus—that fluctuate over time and shape responses, tone, and interaction depth. The Emotional Curve is therefore both a simulation tool and a design constraint that makes cyber pets feel more like consistent, living entities.

From a protocol perspective, the Emotional Curve is partially reflected on-chain via aggregated state markers and configuration parameters, while the finer dynamics are calculated off-chain. The on-chain markers might include baseline temperament settings, thresholds for particular moods, and references to historical trend logs. This hybrid design preserves user privacy—individual conversations and detailed micro-states remain off-chain—while maintaining a verifiable record that the pet’s emotional profile is stable and not arbitrarily reset. Applications can query emotional summaries to adapt UI, notifications, or in-world behavior.

* Emotional Curve elements:
* Baseline temperament (e.g., calm, energetic, sensitive)
* Dynamic mood axes and thresholds
* State transitions triggered by user interactions or time
* Long-term emotional drift representing growth and bonding

Definition: **Emotional Curve** — a temporal model describing how a pet’s internal state changes, shaping its tone and reactions over time.


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