 Bayesian search theory

Bayesian search theory is a framework that uses Bayesian statistics to optimize search efforts when looking for a target or object that may be present in an uncertain environment. It is particularly useful in situations where the location of the target is unknown, and the goal is to maximize the probability of finding it while minimizing search costs. Here are the main concepts and components of Bayesian search theory: 1. **Prior Probability**: This represents our initial belief about the location of the target before any search effort is made.