Game Dynamics Examples

Game dynamics models capture how rules, competition, and matchmaking shape the flow of play. They connect game-theory incentives with hands-on gameplay tuning.

Whether exploring auctions, queue-based matchmaking, or randomness in loot drops, these examples illustrate how small adjustments in strategy or pairing algorithms dramatically alter the player experience.

Select an example to explore it in the playground.

Beginner - Introductory Models

Intermediate - Classic Dynamics

First-Price vs. Vickrey Auctions

Repeated sealed-bid auctions comparing first-price and Vickrey rules with learning agents.

Level: Intermediate

game-theory auction learning incentive simpy

Probes: revenue, allocative_efficiency, truthful_bidding

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Dynamic Difficulty Adjustment

Adaptive encounters that track win rate to keep players challenged.

Level: Intermediate

gameplay reinforcing-loop balancing-loop adaptive game

Stocks: skill, difficulty, retention
Flows: practice gains, difficulty adaptation
Feedback Loops: skill improvement (reinforcing), challenge tuning (balancing)
Probes: skill, difficulty, win_rate, frustration, retention

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