| U. Beyer, F. Smieja, Data exploration with reflective adaptive models, Comput. Statist. Data Anal. 22 (1996) 193--211. |
....or unexpected difficulties. If a system is to display even the smallest semblance of what we recognize to be intelligence , Driver Programs 3 then the ability to cope with unforeseen events is perhaps the most essential ingredient it should possess. Such is the nature of open environments [15, 3], and the robot that acts reasonably under such conditions will need to fulfill different requirements than the standard industrial robot. For most industrial applications the adoption of a full IK solution method does not pose significant problems, since the robots are generally to be used in ....
U. Beyer and F. J. ' Smieja. Data exploration with reflective adaptive models. Computational Statistics and Data Analysis, 22:193-- 211, 1996.
....is the batch solution where all the 400 patterns are presented before the weights are updated with the accumulated back propagation changes, and Figure 5d is the incremental solution, using online back propagation learning. The incremental solution is more desirable for dynamic open problems [1], since the agent adapts after each pattern is seen. A characteristic difference in solution (the generalization) between the two methods is the sharper edges in the incremental method, that separate the MINOS modules contributions. The division of the input space for the solution of Figure 5d is ....
U. Beyer and F. J. ' Smieja. Data exploration with reflective adaptive models. Computational Statistics and Data Analysis, 22:193-- 211, 1996.
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U. Beyer, F. Smieja, Data exploration with reflective adaptive models, Comput. Statist. Data Anal. 22 (1996) 193--211.
No context found.
U. Beyer and F. Smieja, "Data exploration with reflective adaptive models," Computational Statistics Data Analysis, vol. 22, pp. 193--211, 1996.
No context found.
U. Beyer and F. Smieja, Data Exploration with Reflective Adaptive Models, Computational Statistics and Data Analysis, vol. 22, pp. 193-211, 1996.
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