Autonomous search in complex spaces

Abstract

The search for information in a complex system space - such as the Web or large digital libraries, or in an unkown robotics environment - requires the design of efficient and intelligent strategies for (1) determining regions of interest using a variety of sensors, (2) detecting and classifying objects of interest, and (3) searching the space by autonomous agents. This paper discusses strategies for directing autonomous search based on spatio-temporal distributions. We discuss a model for search assuming that the environment is static, except for the effect of identifying object locations. Algorithms are designed and compared for autonomously directing a robot.