Autonomous Search For Information In An Unknown Environment

The search for information in a complex information 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, (2) detecting and classifying information 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, and where the information that agents have is updated as they pursue their discovery of the environment. Autonomous search algorithms are designed and compared using simulations