- author = "Edward Tunstel and Tanya Lippincott and Mo Jamshidi",
- title = "Behavior Hierarchy for Autonomous Mobile Robots: Fuzzy-behavior modulation and evolution",
- journal = "International Journal of Intelligent Automation and Soft Computing, Special Issue: Autonomous Control Engineering at NASA ACE Center",
- year = "1997",
- volume = "3",
- number = "1",
- pages = "37--49",
- keywords = "genetic algorithms, genetic programming",
-
URL = "
http://www-robotics.jpl.nasa.gov/people/Edward_Tunstel/acesi.ps",
- size = "14 pages",
- abstract = "Realization of autonomous behavior in mobile robots, using fuzzy logic control, requires formulation of rules which are collectively responsible for necessary levels of intelligence. Such a collection of rules can be conveniently decomposed and efficiently implemented as a hierarchy of fuzzy-behaviors. This article describes how this can be done using a behavior-based architecture. A behavior hierarchy and mechanisms of control decision-making are described. In addition, an approach to behavior coordination is described with emphasis on evolution of fuzzy coordination rules using the genetic programming (GP) paradigm. Both conventional GP and steady-state GP are applied to evolve a fuzzy-behavior for sensor-based goal-seeking. The usefulness of the behavior hierarchy, and partial design by GP, is evident in performance results of simulated autonomous navigation.",
-
notes = "
",
