Alertness Noise Absence
Defines how alertness noise absence balances risk and reward in stealth encounters.
Overview
This approach to alertness noise absence has been validated across multiple commercial titles and can be adapted to both indie and AAA scopes. Implementation typically involves a state machine or event-driven architecture that tracks alertness noise absence across game sessions. The system scales well from simple implementations to complex multi-layered designs depending on the game's needs for alertness noise absence.
Game Examples
Splinter Cell: Blacklist
Features light-and-shadow based detection mechanics
Metal Gear Solid V
Features multi-layered stealth with buddy and gadget systems
Deus Ex
Implements augmentation-based stealth with hacking alternatives
Pros & Cons
Advantages
- Enables emergent gameplay scenarios
- Creates engaging moment-to-moment gameplay
- Well-documented pattern with proven results
Disadvantages
- Can feel repetitive without sufficient variation
- Requires significant testing and iteration
- May require extensive localization support
Implementation Patterns
Detection Meter
typescriptTracks enemy awareness with multi-state detection
class DetectionSystem {
private awareness = 0;
private readonly THRESHOLD = 100;
update(visibility: number, noise: number, distance: number): State {
const rate = (visibility * 0.5 + noise * 0.3) / Math.max(distance, 1);
this.awareness = clamp(this.awareness + rate, 0, this.THRESHOLD);
if (this.awareness >= this.THRESHOLD) return 'ALERT';
if (this.awareness > 60) return 'SUSPICIOUS';
if (this.awareness > 20) return 'CAUTIOUS';
return 'UNAWARE';
}
}Explore More Mechanics
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