首页> 外国专利> CATEGORIZATION AUTOMATA EMPLOYING NEURONAL GROUP SELECTION WITH REENTRY

CATEGORIZATION AUTOMATA EMPLOYING NEURONAL GROUP SELECTION WITH REENTRY

机译:带入场的分类自动化采用神经元群选择

摘要

An apparatus capable of sensing the presence of objects in its environment, categorizing these objects without a prior description of the categories to be expected, and controlling robotic effector mechanisms to respond differentially to such objects according to their categories. Such responses include sorting objects, rejecting objects of certain types, and detecting novel or deviant objects. The invention includes a device called a "classification n-tuple" (of which a "classification couple" is a special case) capable of combining signals from two or more sensory modalities to arrive at the classification of the object.PPThe invention operates by simulating certain features of animal nervous system, including neurons with responses determined at each moment of time by inputs received along synaptic connections from sensory means or form other neurons. In this invention, neurons are arranged in "groups", which permits them to act cooperatively while still retaining characteristic individual responses. Groups in turn are arranged in "repertoires", which provide a totality of response specificities sufficient to respond to any of a range of possible input objects. Some of these repertoires are organized as "maps", such that groups responding to inputs that are similar along some dimensional (spatial or abstract) are close together in the repertoire, enabling the repertoire to respond correctly to novel objects that are similar to objects it has encountered previously. Maps in this invention are linked by connections, called "reentrant" connections, that enable the responses of one map to be reentered into the system as inputs to another map. Reentrant connections permit signals from different sensory modalities to be correlated in an ongoing fashion, and they are the basis for the operation of classification n-tuples.PPThe responses of the apparatus of this invention may be improved and optimized for a particular task through the operation of "neuronal group selection", a process which enhances the responses of those neuronal groups in the apparatus which were active in some time interval preceding the production of a useful output action. This process operates by modifying the strength of selected synaptic connections. The value of various output actions is determined, for the purpose of regulating selection, by means which are internal to the apparatus of this invention. Accordingly, the invention is capable of self-organization and learning, and does not require a predetermined specification of correct responses for all possible inputs.
机译:一种设备,其能够感测其环境中对象的存在,无需事先对预期类别进行描述就可以对这些对象进行分类,并控制机器人效应器机制根据这些对象的类别对此类对象做出不同的响应。此类响应包括对对象进行分类,拒绝某些类型的对象以及检测新颖或异常的对象。本发明包括一种被称为“分类n元组”的设备(其中“分类对”是特例),该设备能够组合来自两个或多个感官模态的信号以达到物体的分类。 >本发明通过模拟动物神经系统的某些特征来进行操作,包括神经元,该神经元的响应在每个时刻由沿着沿突触连接从感觉装置接收的输入或形成其他神经元的输入确定。在本发明中,神经元被排列成“组”,这允许它们协同作用,同时仍保留特征性的个体反应。依次将组安排在“库”中,这些库提供足以响应任何范围的可能输入对象的响应特异性的整体。这些库中的一些被组织为“地图”,从而使沿某个维度(空间或抽象)相似的输入做出响应的组在库中靠得很近,从而使该库能够正确地响应与该对象相似的新颖对象以前遇到过。本发明中的映射通过称为“可重入”连接的连接链接,该连接使得一个映射的响应能够作为另一映射的输入重新输入到系统中。凹入连接允许来自不同感觉模态的信号以持续的方式相关,并且它们是分类n元组的操作的基础。对于本发明的装置,响应可以被改善和优化。通过“神经元组选择”的操作来完成特定任务,该过程增强了设备中在产生有用输出动作之前的某个时间间隔内处于活动状态的那些神经元组的响应。该过程通过修改所选突触连接的强度来进行。为了调节选择的目的,通过本发明设备内部的手段确定各种输出动作的值。因此,本发明能够自我组织和学习,并且不需要针对所有可能的输入的正确响应的预定规范。

著录项

  • 公开/公告号EP0495901B1

    专利类型

  • 公开/公告日2001-01-03

    原文格式PDF

  • 申请/专利权人 NEUROSCIENCES RES FOUND;

    申请/专利号EP19900916136

  • 发明设计人 EDELMAN GERALD M.;REEKE GEORGE N. JR.;

    申请日1990-10-10

  • 分类号G06F15/18;B25J9/16;

  • 国家 EP

  • 入库时间 2022-08-22 01:17:32

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