# Bayesian Decision-Making

> A formal framework for choosing among actions by combining prior probabilities, observed evidence, and the value or cost of each possible outcome.

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## Definition

A formal framework for choosing among actions by combining prior probabilities, observed evidence, and the value or cost of each possible outcome. Rather than treating beliefs as fixed, a Bayesian decision-maker updates them as new data arrives and selects the action that maximizes expected value under the updated distribution. This framework excels in environments with structured uncertainty — pricing experiments, clinical trials, capital allocation under risk. Its main cost is requiring the decision-maker to make implicit assumptions explicit: priors, likelihoods, and utility functions all have to be written down.

## Related

- [Bayesian reasoning in SynthBoard](https://www.synthboard.ai/glossary/bayesian-reasoning)


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