图 书 馆
信息优化的进化学习Information evolution of optimal learning |
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| 课程网址: | http://videolectures.net/aispds08_belavkin_ieol/ |
| 主讲教师: | Roman V. Belavkin |
| 开课单位: | 米德尔塞克斯大学 |
| 开课时间: | 2008-09-04 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | It is widely accepted that learning is closely related to theories of optimisation and information. Indeed, there is no need to learn if there is nothing to optimise; if one possesses full information, then there is simply nothing new to learn. The paper considers learning as an optimisation problem with dynamical information constraints. Unlike the standard approach in the optimal control theory, where the solutions are given by the Hamilton–Jacobi–Bellman equation for Markov time evolution, the optimal solution is presented as the system of canonical Euler equations defining the optimal information–utility trajectory in the conjugate space. The optimal trajectory is parameterised by theinformation–utility constraints, which are illustrated on examples for finite and infinite–dimensional cases. |
| 关 键 词: | 信息优化; 进化学习 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-10-31：lxf |
| 阅读次数: | 38 |