This paper presents an integrated on line learning system to evolve programmable logic array (PLA) controllers for navigating an autonomous robot in a two dimensional environment. The integrated on line learning sy...This paper presents an integrated on line learning system to evolve programmable logic array (PLA) controllers for navigating an autonomous robot in a two dimensional environment. The integrated on line learning system consists of two learning modules: one is the module of reinforcement learning based on temporal difference learning based on genetic algorithms, and the other is the module of evolutionary learning based on genetic algorithms. The control rules extracted from the module of reinforcement learning can be used as input to the module of evolutionary learning, and quickly implemented by the PLA through on line evolution. The on line evolution has shown promise as a method of learning systems in complex environment. The evolved PLA controllers can successfully navigate the robot to a target in the two dimensional environment while avoiding collisions with randomly positioned obstacles.展开更多
Void nucleation and positronium formation are studied by positron annihilationlifetime technique in α-Al<sub>2</sub>O<sub>3</sub> irradiated by E<sub>n</sub>≥1 MeV fast neutrons t...Void nucleation and positronium formation are studied by positron annihilationlifetime technique in α-Al<sub>2</sub>O<sub>3</sub> irradiated by E<sub>n</sub>≥1 MeV fast neutrons to a fluence of 3×10<sup>20</sup> n/cm<sup>2</sup>.The voids of 0.7 nm are observed in the irradiated α-Al<sub>2</sub>O<sub>3</sub> after the post-irradiationannealing at 850℃ and the positronium is formed in the voids.展开更多
文摘This paper presents an integrated on line learning system to evolve programmable logic array (PLA) controllers for navigating an autonomous robot in a two dimensional environment. The integrated on line learning system consists of two learning modules: one is the module of reinforcement learning based on temporal difference learning based on genetic algorithms, and the other is the module of evolutionary learning based on genetic algorithms. The control rules extracted from the module of reinforcement learning can be used as input to the module of evolutionary learning, and quickly implemented by the PLA through on line evolution. The on line evolution has shown promise as a method of learning systems in complex environment. The evolved PLA controllers can successfully navigate the robot to a target in the two dimensional environment while avoiding collisions with randomly positioned obstacles.
文摘Void nucleation and positronium formation are studied by positron annihilationlifetime technique in α-Al<sub>2</sub>O<sub>3</sub> irradiated by E<sub>n</sub>≥1 MeV fast neutrons to a fluence of 3×10<sup>20</sup> n/cm<sup>2</sup>.The voids of 0.7 nm are observed in the irradiated α-Al<sub>2</sub>O<sub>3</sub> after the post-irradiationannealing at 850℃ and the positronium is formed in the voids.
