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1. CN103295065 - 自主的基于生物学的学习工具

Office
China
Application Number 201310185941.2
Application Date 05.03.2009
Publication Number 103295065
Publication Date 11.09.2013
Grant Number 103295065
Grant Date 28.09.2016
Publication Kind B
IPC
G06N 5/04
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
5Computer systems using knowledge-based models
04Inference methods or devices
G05B 13/02
GPHYSICS
05CONTROLLING; REGULATING
BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
13Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
02electric
CPC
G05B 13/0265
GPHYSICS
05CONTROLLING; REGULATING
BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
13Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
02electric
0265the criterion being a learning criterion
G06N 5/04
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
5Computer systems using knowledge-based models
04Inference methods or devices
G06N 20/00
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
20Machine learning
G06N 5/02
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
5Computer systems using knowledge-based models
02Knowledge representation
Applicants 东京毅力科创株式会社
Inventors S·考歇尔
S·J·帕特尔
杉岛贤次
Agents 上海专利商标事务所有限公司 31100
Priority Data 12044958 08.03.2008 US
Title
(ZH) 自主的基于生物学的学习工具
Abstract
(ZH)
自主的基于生物学的学习工具。提供了一种自主的基于生物学的学习工具系统和该工具系统用来进行学习和分析的方法。自主的基于生物学的学习工具系统包括(a)执行一组特定任务或过程并生成资产和与资产相关的表征各过程和相关联的工具性能的数据的一个或多个工具系统;(b)接收并格式化数据的交互管理器,以及(c)基于生物学习原理的自主学习系统,这样的系统包括被递归地定义并通过网络进行通信的存储器平台和处理平台。自主工具系统可以递归地部署以组装日益复杂的自主工具。在与单独的或组装的复杂自主工具相关联的自主学习系统中生成和累积的知识可以被投放到可用于学习并基于上下文驱动工具目标的语义网络中。