Feedback

Mechanism · IX – Learning & Adaptation immediate / delayed / absent / aggregated · reversible · open / asymmetric · solo / cooperative / competitive

Feedback reports back to agents the results of their actions: action and game state become a signal to the agents; the aim is that they learn from it and adapt their behaviour.

Design question – How does your game report the results of agents’ actions back to them – and how does that shape their behaviour?

Reference example – Wordle: green, yellow and grey show after each guess which letters are right. Guitar Hero: hit notes light up, missed ones sound off, the crowd cheers or boos. Jenga: the tower wobbles – it signals danger before it falls. Mario Kart (Catch-Up / Rubber Banding) · Pandemic (Progressive Difficulty) · Wingspan Solo (Solo Mode (Automa))

Structural pattern

Input -> transformation -> output: an action and the game state become a behavioural adaptation (learning, reacting) via a response (signal).

Regulated mainly in conditioning mode (a result or state feeds back, reinforcing or dampening; thresholds trigger the feedback) and constraining mode (how much is fed back; with what delay). The channel in which the feedback appears (visual, auditory, haptic) is appearance; in a game, thresholds and delay become specifications.

Design parameters

• Timing – immediate ↔ only at the end
• Content – precise (exact value) ↔ binary (good/bad)
• Direction – positive (reinforcing) ↔ negative (dampening)
• Addressee – individual ↔ asymmetric
• Modality – visual ↔ multimodal
• Granularity – per action ↔ only at the end

Related Mechanisms

• Scoring (MEC-09) – Frequently combined: points as feedback.
• Monitoring (MEC-19) – Frequently combined: data as a feedback source.
• Decay (MEC-04) – Frequently combined: feedback about decay.
• Progression (MEC-15) – Frequently combined: feedback about progress.

Ludic Organisational Structures

Ecosystem · Reputation / Trust System (core)