Learning Process Enhancement for Robot Behaviors

Designing a simulated system and training it to optimize its tasks in simulated environment helps the designers to avoid problems that may appear when designing the system directly in real world. These problems are: time consuming, high cost, high errors percentage and low efficiency and accuracy of the system. The proposed system will investigate and improve the efficiency and accuracy of a simulated robot to choose correct behavior to perform its task. In this paper, machine learning, which uses genetic algorithm, is adopted. This type of machine learning is called genetic-based machine learning in which a distributed classifier system is used to improve the efficiency and accuracy of the robot. Consequently, it helps the robot to achieve optimal action.

Authors:

• Saeed Mohammed Baneamoon
• Rosalina Abdul Salam
• Abdullah Zawawi Hj. Talib

Keywords:

• Machine Learning
• Genetic-Based MachineLearning
• Learning Classifier System
• Behaviors.

References:

[1] Goldberg, D. E. "Genetic Algorithms in Search, Optimization, and
Machine Learning". Addison-Wesley, Reading, Mass. .1989.
[2] Luger & Stubblefield "Artificial Intelligence (Structures and strategies
for complex problem solving ) " Addison Wesley Longman, Inc., 1998.
[3] Marco Dorigo & Marco Colombetti , "Robot shaping ( An experiment
in behavior engineering ) " The MIT Press , Cambridge, Massachusetts,
London, England, 1998.
[4] Marco Dorigo, "Genetic-Based Machine Learning and Behavior-Based
Robotics: A New Synthesis", 0018-9472/93, IEEE Transactions on
System, Man, and Cybernetics. Vol. 23, No. 1, January/ February 1993.
[5] John S. Bay, "Learning Classifier Systems for Single and Multiple
Mobile Robots in Unstructured Environments" Mobile Robots X,
Philadelphia, PA, Nov. 1995, pp. 88-99.
[6] D. E. Goldberg. "Sizing populations for serial and parallel genetic
algorithms" - Third international conference on genetic algorithms,
1989.
[7] Alan C. Schultz. "Learning robot behaviors using genetic algorithms "-
The international symposium on robotics and manufacturing , 1994.
[8] Gabriel Robert, Pierre Portier, Agens Guillot, "Classifier Systems as
ÔÇÿANIMAT- Architectures for action selection in MMORPG" -
AnimatLab, Laboratorie d-Informatique de Paris, France, 2002.
[9] Larry Bull, "Learning Classifier Systems: A Brief Introduction" -
Faculty of Computing Engineering & Mathematical Sciences, University
of the West of England, U.K, 2003.
[10] Petr Musilek, Sa Li, and Loren Wyard-Scott, "Enhanced Learning
Classifier System for Robot Navigation" - Department of Electrical and
Computer Engineering, University of Alberta, Canada, 200.