Use this game-theory utility to inspect best responses or pure-strategy equilibria in a finite payoff model whose players, actions, and utilities are specified explicitly.

Row-player payoffs

Required list input.

Column-player payoffs

Required list input.

Initial row action

Required integer input.

Initial column action

Required integer input.

Iterations

Required integer input.

Iteratively choose pure best responses in a two-player normal-form game. The tool evaluates the supplied inputs together and returns the named outputs below; it does not infer omitted operating conditions or change the units shown.^[1]

Best-response trace

The resulting best-response trace returned as an object.

• Pure equilibria may not exist or may be multiple, and best-response dynamics need not converge. Results depend on complete and accurate payoffs and do not by themselves predict behavior, learning, bargaining, or mixed strategies.
• Use finite inputs in the displayed units and preserve more precision than the final presentation requires. Independently verify safety-critical, financial, compliance, or production decisions.

Inspect mixed equilibria and sensitivity to payoff changes, and compare model predictions with institutional constraints or observed behavior.

• Pure-Strategy Nash Equilibrium Calculator

  Find every pure-strategy Nash equilibrium in a finite two-player normal-form game, including tied best responses. Strategy indices are zero-based; mixed-strategy equilibria are not computed.

• LD50 Log-Dose Interpolation

  Estimate LD50 by linear interpolation of response against log10 dose between an ordered lower point at or below 50% mortality and an ordered higher point at or above 50%. This is a two-point estimate, not a fitted dose-response model.

• Probit LD50 Estimate

  Calculate LD50 from a fitted probit-5 model of the form probit = intercept + slope × log10(dose). Fifty percent response is probit 5, so LD50 = 10^((5 − intercept)/slope).