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22-Challenge Roadmap
♟️ Game Theory
The mathematics of strategic interaction. From Nash equilibria and auction design to evolutionary dynamics and mechanism design — the tools that power markets, protocols, and multi-agent AI.
🌹 Phase 1: Strategic Foundations (1–10)
Nash equilibria, dominant strategies, backward induction, and auction theory from first principles.
🟠 Phase 2: Repeated Games & Learning (11–14)
Evolutionary stability, replicator dynamics, Q-learning in games, and signalling theory.
🟣 Phase 3: Mechanism Design & Applications (15–20)
VCG, Myerson optimal auctions, Arrow's impossibility, network effects, Nash bargaining, and mean field games.
⭐ Capstone (21–22)
Apply everything: design a complete incentive-compatible marketplace, then train multi-agent reinforcement learning agents and study convergence to Nash equilibria.