An Information-Theoretic-based Evolutionary Approach for the Dynamic Search Path Planning Problem

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Authors
  1. Barkaoui, M.
  2. Berger, J.
Corporate Authors
Defence Research and Development Canada, Valcartier Research Centre, Quebec QC (CAN)
Abstract
A new information-theoretic-based evolutionary approach is proposed to solve the dynamic search path planning problem. Path planning is achieved using an open-loop model with anticipated feedback while dynamically capturing incoming new requests and real action outcomes/observations as exogenous events, to timely adjust search path plans using coevolution. The approach takes advantage of objective function separability and conditional observation probability independence to efficiently minimize expected system entropy, lateness and travel/discovery time respectively. Computational results clearly show the value of the approach in comparison to a myopic heuristics over various problem instances.
Keywords
information theory;evolutionary computation;search path planning
Report Number
DRDC-RDDC-2014-P8 — External Literature
Date of publication
01 May 2014
Number of Pages
7
DSTKIM No
CA039043
CANDIS No
539273
Format(s):
Electronic Document(PDF)

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