nash-equilibrium #

Shows a 2×2 strategy profile payoff matrix. A moving selection box represents the current strategy profile s=(s1,s2). Animated best-response arrows illustrate unilateral deviations: first Player 1’s best response to s−1, then Player 2’s best response to s−2. When both arrows point back to the selected cell, the panel confirms the Nash equilibrium condition (no profitable unilateral deviation) using the best-response inequalities.

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⏮◀◀▶▶STEP0.25x1xZOOM

t=0s

practical uses #

01.Predicting stable outcomes in competitive pricing or bidding (no firm wants to change price alone)
02.Analyzing strategic choices in cybersecurity/defense where unilateral changes may be exploitable
03.Understanding equilibria in mechanism design and auctions (checking for profitable deviations)

technical notes #

Pure Canvas2D. Uses a 4-scene loop (~4s) with ease() for smooth transitions. Best responses are computed from the payoff matrix each frame; arrows and selection are grid-snapped for a blocky aesthetic. Responsive scaling via scale=Math.min(w,h)/baseSize.

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