[1]
Henrich D., Wurll Ch., Woern H. 6 DOF path planning in dynamic environments-A parallel on-line approach. Proceedings of IEEE International Conference on Robotics and Automation (ICRA-98), Leuven, Belgium, (1998).
DOI: 10.1109/robot.1998.676417
Google Scholar
[2]
Hwang Y.K., Ahuja N. Gross motion planning-A survey. ACM Computing Surveys, 1992(24).
Google Scholar
[3]
Kamal L., Gupta K., del Pobil, A.P. Practical motion planning in robotics: Current approaches and future directions, IEEE Robotics & Automation Magazine, (1996).
Google Scholar
[4]
Chen P., Hwang Y.K. A Dynamic Graph Search Algorithm for Motion Planning, IEEE Transaction on Robotics and Automation, 1998(14).
Google Scholar
[5]
Richard.S. Sutton, Andrew.G. Barto. Reinforcement Learning: An Introduction. MIT Press, (1998).
Google Scholar
[6]
Tong liang. A Speedup Convergent Method for Multi-Agent Reinforcement Learning. IEEE Conferences On Information Engineering and Computer Science(ICIECS), Wuhan, 2009(2).
DOI: 10.1109/iciecs.2009.5365958
Google Scholar
[7]
J.C. Santamaria, R.S. Sutton. Experiments with reinforcement learning in problems with continuous state and action spaces. Adaptive Behavior, 1998(6).
Google Scholar
[8]
Hado van Hasselt, MarcoWiering. Reinforcement learning in continuous action spaces. IEEE Symposium on Approximate Dynamic Programming and Reinforcement Learning, (2007).
DOI: 10.1109/adprl.2007.368199
Google Scholar
[9]
Helge Ritter, Thomas Martinetz, and Klaus Schulten. Neural Computation and Self-Organizing Maps: An Introduction. Addison-Wesley, (1992).
Google Scholar
[10]
Baginski,B. Motion Planning for Manipulators with Many Degrees of Freedom, Dissertation, Fakultät für Informatik, Technische Universität München, (1998).
Google Scholar
