Cognition · Software component

User Need Predictor

Software componentCognitionCognition & Memoryarc:UserNeedPredictor

A predictive component that forecasts upcoming user needs, and when users will recognise them, from historical trajectories and current state across immediate, medium-term and long-term horizons.

Responsibility. Forecasts what a user will need and when, to enable well-timed anticipatory assistance.

Also known as: Predictive intelligence, Need forecaster, Anticipation engine

Direct neighbourhood (hover for relationship types)

Relationships

hosts structural

User Trajectory Model Ch10.2

reads dependency

receives data from dynamic

Situational Context Integrator Ch10.2

triggers dynamic

is monitored by assurance

Fairness Monitor Ch10.2

Design guidance

SHOULD use different data sources per horizon: real-time streams for minutes-hours, behavioural history for days-weeks, trend analysis for months.
SHOULD acknowledge irreducible ambiguity in behavioural signals and infer needs from multiple contextual signals rather than a single cue.
MUST be continuously monitored for data quality and periodically retrained, because historical patterns encode bias and go stale.

Quantitative guidance

As stated by the sources; verify before use.

Example trajectories: users reviewing portfolios on Monday mornings check retirement allocations within 2-3 hours; patients with recent medication changes need follow-up within 7 days (Ch10.2).

Classification

Patterns: Trajectory-based predictionMulti-horizon prediction (immediate, medium-term, long-term)
Quality attributes: Performance efficiency (ISO/IEC 25010)Interaction capability (ISO/IEC 25010)
Risks mitigated: Reactive firefightingBias amplification from historical dataStale patterns

Sources

Ch10.2: T. Nguyen, "Proactive Agents," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 10.2. ISBN: 9798244538229.