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Can I read A Reinforcement Learning with Evolutionary State Recruitment Strategy for Autonomous Mobile Robots Control on EtoBox?
A Reinforcement Learning with Evolutionary State Recruitment Strategy for Autonomous Mobile Robots Control by Toshiyuki Kondo; Koji Ito is a Engineering article available to read on EtoBox.
What is A Reinforcement Learning with Evolutionary State Recruitment Strategy for Autonomous Mobile Robots Control about?
In recent robotics fields, much attention has been focused on utilizing reinforcement learning (RL) for designing robot controllers, since environments where the robots will be situated in should be unpredictable for human designers in advance. However there exist some difficulties. One of them is well known as 'curse of dimensionality problem'. Thus, in order to adopt RL for complicated systems, not only 'adaptability' but also 'computational efficiencies' should be taken into account. The paper proposes an adaptive state recruitment strategy for NGnet-based actor-critic RL. The strategy enables the learning system to rearrange/divide its state space gradually according to the task complexity and the progress of learning. Some simulation results and real robot implementations show the validity of the method.
Who reads A Reinforcement Learning with Evolutionary State Recruitment Strategy for Autonomous Mobile Robots Control?
It is typically read by researchers, students, and practitioners in Engineering.
- Author
- Toshiyuki Kondo; Koji Ito
- Publisher
- Elsevier Science; Elsevier ; Elsevier BV (ISSN 0921-8890)
- Published
- 2004
- Language
- EN
- Field
- Engineering (Physical Sciences)