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Average search time bounds in cue-based searches.

Vaibhav Wasnik1

  • 1Indian Institute of Technology Goa, Ponda 403401, Goa, India.

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|March 19, 2021
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Summary
This summary is machine-generated.

This study introduces a search strategy that uses probability distributions to find a source. The lower bound on search time is found to be related to the distribution

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Area of Science:

  • Search theory
  • Probability distributions
  • Information theory

Background:

  • Search problems often involve uncertainty about the target's location.
  • Effective search strategies can minimize time and resources.
  • Probability distributions are key to understanding search space.

Purpose of the Study:

  • To develop and analyze search strategies based on probability distributions.
  • To derive a lower bound on search time for different strategies.
  • To investigate the relationship between search efficiency and information entropy.

Main Methods:

  • Modeling search as a step-by-step process with neighborhood movement.
  • Defining jump probability based on the difference in source probability at locations.
  • Deriving analytical expressions for the lower bound on average search time.

Main Results:

  • A lower bound on search time was evaluated for a neighborhood-based strategy.
  • An expression for the lower bound was derived for a generic strategy utilizing probability distributions.
  • For diffusing particles in a homogeneous medium, the lower bound scales with e^(E/2), where E is the entropy of the probability distribution.

Conclusions:

  • Search time lower bounds can be analytically determined using probability distributions.
  • Information entropy (E) is a critical factor influencing search efficiency.
  • The derived relationship provides a theoretical limit for optimizing search strategies.