---
title: "Laplace criterion"
source: "https://systems-analysis.info/eng/Laplace_criterion"
wiki: "systems-analysis.info/eng"
article: "Laplace_criterion"
language: "en"
categories:
  - "Category:Decision theory"
  - "Category:Decision-making"
  - "Category:English"
  - "Category:Science"
revision_id: 210
wiki_created_at: 2026-09-06T22:18:57Z
wiki_modified_at: 2026-09-06T22:18:57Z
downloaded_at: 2026-09-07T22:21:53Z
---

# Laplace criterion

**Laplace's Criterion** is a decision-making method under uncertainty based on the assumption that all possible outcomes are equally likely.

## Essence of the Criterion

Laplace's criterion assumes that if there is no information about the probabilities of different outcomes, it is reasonable to consider them equal. For each strategy, its average result across all possible outcomes is then calculated.

In other words, each outcome is considered equally probable, and the strategy is chosen based on the maximum average result.

## Applying the Criterion

The application process includes the following steps:

1.  For each strategy, all possible outcomes are summed up.
2.  The resulting sum is divided by the number of outcomes to determine the average value.
3.  The strategy with the highest average result is selected.

Thus, Laplace's criterion reflects a neutral approach, with no tendency toward optimism or pessimism.

## Advantages and Disadvantages

**Advantages:**

- Simplicity and logical application when there is no information about probabilities.
- Balanced assessment of all outcomes.

**Disadvantages:**

- The assumption of equally probable outcomes often does not correspond to reality.
- It ignores the specifics of individual outcomes that may be of critical importance.

## See also

- [Bayes criterion](https://systems-analysis.info/eng/Bayes_criterion "Bayes criterion")
- [Bayes minimax criterion](https://systems-analysis.info/eng/Bayes_minimax_criterion "Bayes minimax criterion")
- [Criterion](https://systems-analysis.info/eng/Criterion "Criterion")
- [Hodges-Lehmann criterion](https://systems-analysis.info/eng/Hodges-Lehmann_criterion "Hodges-Lehmann criterion")