Core Idea
Definition
Minimax seeks to minimize the maximum possible loss, while maximin seeks to maximize the minimum guaranteed payoff among available options.
In Plain English
When uncertainty is serious, you may choose the path that leaves you least exposed in the worst case or gives you the best floor.
How It Works
Many decision tools assume you can estimate probabilities reliably. Minimax and maximin become useful when that assumption is weak, when losses could be severe, or when survivability matters more than upside. Instead of focusing on expected averages, you compare the worst plausible outcome of each option. If one path has a painful but survivable floor while another has a small chance of catastrophe, a cautious decision-maker may prefer the safer floor. This is particularly relevant in conflict, negotiation, safety, and situations where a single bad result can dominate all other considerations.
When to Use
- •When probabilities are unclear or unreliable
- •When worst-case downside is especially important
- •When survival or continuity matters more than optimization
- •When comparing options with dramatically different risk floors
- •When a single severe failure would overwhelm many small wins
Examples
Everyday
If choosing between a route home you know well and one that might save a few minutes but carries a serious risk of getting lost before an important event, you may prefer the safer floor.
Professional
A company with limited runway may reject a flashy strategy with huge upside if the downside could end the business before learning occurs.
Extreme Case
In safety-critical operations, a plan that limits the worst possible failure is often preferable even if it is less efficient in average conditions.
Common Mistakes
- •Using worst-case thinking for low-stakes reversible decisions
- •Letting imagined disasters dominate without checking realism
- •Ignoring opportunity cost while protecting against unlikely harms
- •Confusing emotional discomfort with a genuinely unacceptable downside
Limits & Failure Modes
- •The rule can be too conservative in situations where upside matters and probabilities are knowable
- •Worst-case scenarios can be exaggerated unrealistically
- •Minimax may sacrifice large long-run value to avoid discomfort rather than true danger
- •It is weaker when the real objective requires growth rather than just protection
How to Practice
floor first
For each option, identify the minimum acceptable outcome and eliminate paths that fall beneath it.
worst case realism
Stress-test your worst-case assumptions so you do not optimize against fantasy disasters.
survival before upside
When continuity matters, prioritize staying in the game before chasing additional gains.
Related Cognitive Biases
loss aversion
People naturally weight downside heavily, but minimax makes that weighting explicit and structured rather than purely emotional.
optimism bias
The model counters the tendency to focus on upside without respecting the severe downside case.
normalcy bias
People may assume the worst case is irrelevant because recent outcomes were ordinary.
Related Mental Models
Related Skills
Advanced Notes
Historical Origin
These rules appear in decision theory, game theory, and strategic planning under uncertainty.
Philosophical Context
They reflect a conservative orientation toward choice where the downside boundary, not the average outcome, anchors rational action.
Further Reading
- Thinking in Bets by Annie Duke
- The Strategy of Conflict by Thomas C. Schelling
- Against the Gods by Peter L. Bernstein