Optimal Search Models

Abstract

A target is located in one of n boxes. Initially, the target is in box i with a given prior probability p(sub i)(sup 0), the summation of P(sub i) (sup 0) = 1. A sequential search is made. Searching box i costs (c sub 1) > 0 and finds the target with probability (alpha sub i) (i.e., the overlook probability is 1 - (alpha sub i)) if the target is in the box at that time. A reward (R sub i) is earned if the target is found in box i. A strategy is any rule for determining when to search, and if so, which box. The objective is to maximize the probability of finding the target in a given number of searches or to minimize the risk (expected searching cost minus expected reward).

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1972
Accession Number
AD0746151

Entities

People

  • Yi Chi Kan

Organizations

  • University of California, Berkeley

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • California
  • Detection
  • Dynamic Programming
  • Mathematical Models
  • Models
  • Moving Targets
  • Operations Research
  • Probability
  • Probability Distributions
  • Random Variables
  • Sequences
  • Stationary
  • Targets
  • Transitions
  • United States
  • United States Government

Fields of Study

  • Computer science

Readers

  • Analytical Mechanics
  • Regression Analysis.
  • Sensor Fusion and Tracking Systems.