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Game Theory Basics

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game theory normal form payoff matrix dominant strategy prisoners dilemma

Core Idea

Game theory studies strategic interactions where each player's payoff depends on the choices of all players. A game in normal form specifies players, strategies, and payoffs in a matrix. A dominant strategy is one that is optimal regardless of what the opponent does. The Prisoner's Dilemma is the canonical example where individual dominant strategies lead to a mutually inferior outcome, illustrating why coordination problems and market failures arise even among rational agents.

How It's Best Learned

Work through the Prisoner's Dilemma payoff matrix by hand, identifying dominant strategies before defining Nash equilibrium. Then apply the framework to advertising decisions, pricing, and arms-race scenarios.

Common Misconceptions

Explainer

Game theory studies decision-making in strategic interactions — situations where your payoff depends not just on your own choice but on the choices of others. This distinguishes it from the optimization problems you've seen elsewhere in microeconomics, where you simply maximize utility or profit given fixed prices and constraints. In strategic situations, your best action depends on what others do, and their best action depends on what you do. Game theory provides the tools to analyze this mutual dependence precisely.

Every game in normal form has three elements: players, strategies, and payoffs. A payoff matrix displays this information visually. Each row is a strategy for player 1, each column is a strategy for player 2, and each cell shows what both players earn for that combination of choices. Reading the matrix is itself a skill — by convention, the row player's payoff is listed first. Before solving any game, spend a moment mapping out what each cell means in terms of the actual situation being modeled.

A dominant strategy is one that is optimal regardless of what the opponent does. To identify it: compare each strategy of player 1 across all columns. If one row always gives a payoff at least as high as every other row, that row dominates. When a dominant strategy exists, a rational player should always choose it — no prediction about the opponent is needed. This makes dominant-strategy reasoning especially robust. Most games, however, do not have dominant strategies for all players, which is why Nash equilibrium (a concept you'll study next) is the more general solution concept.

The Prisoner's Dilemma is the most important example in introductory game theory precisely because it exposes the limits of individual rationality. Each player has a dominant strategy — defect. Both play it. But the result (mutual defection) is worse for both than if they had cooperated. The core insight: individual rationality does not guarantee collective optimality. You've already seen this idea in the context of market failures and public goods: the rational choice for each individual (free-ride, pollute, defect) undermines the outcome for everyone. The Prisoner's Dilemma gives that intuition mathematical precision.

This framework applies far beyond stylized examples. Firms deciding whether to advertise, countries choosing military spending levels, and commuters choosing routes all face Prisoner's Dilemma-style structures. In each case, the temptation to defect is individually rational but collectively costly. Understanding this structure tells you when regulation, contracts, or repeated interaction might enable better outcomes — because when the game is played repeatedly, the calculus changes and cooperation can become self-sustaining. That extension is where the analysis gets richer.

Practice Questions 3 questions

Prerequisite Chain

Understanding Zero → The Number Zero → Counting to Five → Counting to 10 → Counting to 20 → Counting a Set of Objects Up to 20 → Cardinality: The Last Number Counted → Matching Numerals to Quantities → Subitizing Small Quantities → Addition Within 10 → Number Bonds to 10 → Addition Within 20 → Doubles and Near Doubles → Doubles Facts Within 10 → Near Doubles Facts Within 20 → Mental Math Strategies for Addition → Mental Math: Adding and Subtracting Tens → Addition Within 100 → Repeated Addition as Multiplication → Multiplication as Equal Groups → Multiplication: Arrays → Basic Multiplication Facts (0s, 1s, 2s, 5s, 10s) → Multiplication Facts Within 100 → Division as Equal Sharing → Division as Grouping (Measurement Division) → Division: Grouping (Repeated Subtraction) Model → Division: Fair Sharing Model → Division as Equal Sharing → Division as Grouping → Basic Division Facts → Division Facts Within 100 → Multiplication and Division Fact Families → Relationship Between Multiplication and Division → Division Facts as Inverse of Multiplication → Remainders and Quotients in Division → Division Word Problems → Multi-Step Word Problems → Solving Multi-Step Word Problems → Multiplication Word Problems → Division Word Problems → Introduction to Long Division → Factors and Multiples → Prime and Composite Numbers → Equivalent Fractions → Relating Fractions and Decimals → Decimal Place Value → Integers and the Number Line → Comparing and Ordering Integers → Absolute Value → Adding Integers → Subtracting Integers → Multiplying Integers → Dividing Integers → Unit Rates → Proportions → Percent Concept → Converting Between Fractions, Decimals, and Percents → Operations with Rational Numbers → Two-Step Equations → Solving Multi-Step Equations → Equations with Variables on Both Sides → Literal Equations → Slope-Intercept Form → Point-Slope Form → Writing Linear Equations → Parallel and Perpendicular Line Slopes → Graphing Linear Equations → Piecewise Functions → One-Sided Limits → Continuity Definition → Limits and Continuity in Multiple Variables → Functions of Several Variables → Continuity in Multiple Variables → Partial Derivatives: Definition and Computation → Differentiability in Multiple Variables → Differentiability in Multivariable Functions → Total Differential and Linear Approximation → Chain Rule for Multivariable Functions → Implicit Differentiation → Related Rates → Optimization Problems → Critical Points of Multivariable Functions → Critical Points and Classification of Extrema → Second Partial Test for Local Extrema (Hessian) → The Hessian Matrix and Second Derivative Test → Unconstrained Optimization: Finding Extrema → Optimization in Multiple Variables → Lagrange Multipliers → Constrained Optimization and Lagrange Multipliers → Utility and Preferences → Marginal Utility and Diminishing Returns → Profit Maximization → Perfect Competition → Shutdown and Breakeven Decisions → Monopoly → Monopolistic Competition → Oligopoly and Strategic Behavior → Game Theory Basics

Longest path: 98 steps · 520 total prerequisite topics

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