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1. 发明授权

US08019713B2 Commonsense reasoning about task instructions 有权
标题翻译：关于任务说明的常识推理
公开(公告)号：US08019713B2
公开(公告)日：2011-09-13
申请号：US11378063
申请日：2006-03-16
申请人： Rakesh Gupta , Ken Hennacy
发明人： Rakesh Gupta , Ken Hennacy
IPC分类号： G06N5/02
CPC分类号： G06N5/00
摘要： A system and method enable an autonomous machine such as an indoor humanoid robot to systematically process user commands and respond to situations. The method captures distributed knowledge from human volunteers, referred to as “commonsense knowledge.” The commonsense knowledge comprises classes such as steps for tasks, responses to situations, and locations and uses of objects. Filtering refines the commonsense knowledge into useful class rules. A second level of rules referred to as meta-rules performs reasoning by responding to user commands or observed situations, orchestrating the class rules and generating a sequence of task steps. A task sequencer processes the generated task steps and drives the mechanical systems of the autonomous machine.
摘要翻译：系统和方法使得诸如室内人形机器人的自主机器能够系统地处理用户命令并对情况做出响应。该方法捕获来自人类志愿者的分布式知识，被称为“常识知识”。常识知识包括诸如任务步骤，对情境的反应以及对象的位置和用途等类。过滤将常识知识细化为有用的类规则。称为元规则的第二级规则通过响应用户命令或观察到的情况来执行推理，协调类规则并生成一系列任务步骤。任务排序器处理生成的任务步骤并驱动自主机器的机械系统。

2. 发明申请

US20080294590A1 Reluctant Episodic Memory (REM) to Store Experiences of Everyday Interaction With Objects 有权
标题翻译：不寻常的剧情记忆（REM）存储与对象日常互动的经验
公开(公告)号：US20080294590A1
公开(公告)日：2008-11-27
申请号：US11859034
申请日：2007-09-21
申请人： Rakesh Gupta , Ken Hennacy
发明人： Rakesh Gupta , Ken Hennacy
IPC分类号： G06N7/00
CPC分类号： G06N5/02 , G06N3/02
摘要： A method and system for storing episodic sequences (events and actions). The system learns episodic sequencing by observing real-world events and actions or by receiving fact data from a database storing common sense facts. The episodic sequences are classified into events and actions, processed to indicate correlations and causality between the events and actions, and generated into linked graphs. The linked graphs may then be used to draw inferences, recognize patterns, and make decisions.
摘要翻译：用于存储情景序列（事件和动作）的方法和系统。系统通过观察现实世界的事件和动作或通过从存储常识事实的数据库接收事实数据来学习情景排序。情景序列分为事件和动作，处理以指示事件和动作之间的相关性和因果关系，并生成链接图。然后可以使用链接的图形来绘制推论，识别模式并作出决定。

3. 发明授权

US07957968B2 Automatic grammar generation using distributedly collected knowledge 有权
标题翻译：使用分布式收集知识的自动语法生成
公开(公告)号：US07957968B2
公开(公告)日：2011-06-07
申请号：US11609683
申请日：2006-12-12
申请人： Rakesh Gupta , Ken Hennacy
发明人： Rakesh Gupta , Ken Hennacy
IPC分类号： G10L15/06
CPC分类号： G06F17/27
摘要： The invention includes a computer based system or method for automatically generating a grammar associated with a first task comprising the steps of: receiving first data representing the first task based from responses received from a distributed network; automatically tagging the first data into parts of speech to form first tagged data; identifying filler words and core words from said first tagged data; modeling sentence structure based upon said first tagged data using a first set of rules; identifying synonyms of said core words; and creating the grammar for the first task using said modeled sentence structure, first tagged data and said synonyms.
摘要翻译：本发明包括一种用于自动生成与第一任务相关联的语法的基于计算机的系统或方法，包括以下步骤：基于从分布式网络接收的响应接收表示第一任务的第一数据; 自动地将第一数据标记成部分语音以形成第一标记数据; 从所述第一标记数据识别填充词和核心词; 基于使用第一组规则的所述第一标记数据的建模句子结构; 识别所述核心词的同义词; 并且使用所述建模的句子结构，第一标记数据和所述同义词来创建用于第一任务的语法。

4. 发明申请

US20070022078A1 Commonsense reasoning about task instructions 有权
标题翻译：关于任务说明的常识推理
公开(公告)号：US20070022078A1
公开(公告)日：2007-01-25
申请号：US11378063
申请日：2006-03-16
申请人： Rakesh Gupta , Ken Hennacy
发明人： Rakesh Gupta , Ken Hennacy
IPC分类号： G06N7/00 , G06F17/00
CPC分类号： G06N5/00
摘要： A system and method enable an autonomous machine such as an indoor humanoid robot to systematically process user commands and respond to situations. The method captures distributed knowledge from human volunteers, referred to as “commonsense knowledge.” The commonsense knowledge comprises classes such as steps for tasks, responses to situations, and locations and uses of objects. Filtering refines the commonsense knowledge into useful class rules. A second level of rules referred to as meta-rules performs reasoning by responding to user commands or observed situations, orchestrating the class rules and generating a sequence of task steps. A task sequencer processes the generated task steps and drives the mechanical systems of the autonomous machine.
摘要翻译：系统和方法使得诸如室内人形机器人的自主机器能够系统地处理用户命令并对情况做出响应。该方法捕获来自人类志愿者的分布式知识，被称为“常识知识”。常识知识包括诸如任务步骤，对情境的响应以及对象的位置和用途等类。过滤将常识知识细化为有用的类规则。称为元规则的第二级规则通过响应用户命令或观察到的情况来执行推理，协调类规则并生成一系列任务步骤。任务排序器处理生成的任务步骤并驱动自主机器的机械系统。

5. 发明授权

US07974938B2 Reluctant episodic memory (REM) to store experiences of everyday interaction with objects 有权
标题翻译：不情愿的记忆（REM），用于存储与对象日常交互的经验
公开(公告)号：US07974938B2
公开(公告)日：2011-07-05
申请号：US11859034
申请日：2007-09-21
申请人： Rakesh Gupta , Ken Hennacy
发明人： Rakesh Gupta , Ken Hennacy
IPC分类号： G06N5/00
CPC分类号： G06N5/02 , G06N3/02
摘要： A method and system for storing episodic sequences (events and actions). The system learns episodic sequencing by observing real-world events and actions or by receiving fact data from a database storing common sense facts. The episodic sequences are classified into events and actions, processed to indicate correlations and causality between the events and actions, and generated into linked graphs. The linked graphs may then be used to draw inferences, recognize patterns, and make decisions.
摘要翻译：用于存储情景序列（事件和动作）的方法和系统。系统通过观察现实世界的事件和动作或通过从存储常识事实的数据库接收事实数据来学习情景排序。情景序列分为事件和动作，处理以指示事件和动作之间的相关性和因果关系，并生成链接图。然后可以使用链接的图形来绘制推论，识别模式并作出决定。

6. 发明申请

US20070179777A1 Automatic Grammar Generation Using Distributedly Collected Knowledge 有权
标题翻译：使用分布式收集知识的自动语法生成
公开(公告)号：US20070179777A1
公开(公告)日：2007-08-02
申请号：US11609683
申请日：2006-12-12
申请人： Rakesh Gupta , Ken Hennacy
发明人： Rakesh Gupta , Ken Hennacy
IPC分类号： G06F17/27
CPC分类号： G06F17/27
摘要： The invention includes a computer based system or method for automatically generating a grammar associated with a first task comprising the steps of: receiving first data representing the first task based from responses received from a distributed network; automatically tagging the first data into parts of speech to form first tagged data; identifying filler words and core words from said first tagged data; modeling sentence structure based upon said first tagged data using a first set of rules; identifying synonyms of said core words; and creating the grammar for the first task using said modeled sentence structure, first tagged data and said synonyms.
摘要翻译：本发明包括一种用于自动生成与第一任务相关联的语法的基于计算机的系统或方法，包括以下步骤：基于从分布式网络接收的响应来接收表示第一任务的第一数据; 自动地将第一数据标记成部分语音以形成第一标记数据; 从所述第一标记数据识别填充词和核心词; 基于使用第一组规则的所述第一标记数据的建模句子结构; 识别所述核心词的同义词; 并且使用所述建模的句子结构，第一标记数据和所述同义词来创建用于第一任务的语法。

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