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1. 发明授权

US07925984B2 Remote configuration of intelligent software agents 失效
标题翻译：智能软件代理的远程配置
公开(公告)号：US07925984B2
公开(公告)日：2011-04-12
申请号：US10403950
申请日：2003-03-31
申请人： Jeffrey T. Awe , Joseph P. Bigus , Anthony M. Dunbar , Gregory R. Hintermeister , Jacob Kugel , Donald A. Schlosnagle
发明人： Jeffrey T. Awe , Joseph P. Bigus , Anthony M. Dunbar , Gregory R. Hintermeister , Jacob Kugel , Donald A. Schlosnagle
IPC分类号： G06F3/00 , G06F9/00 , G06F17/00
CPC分类号： H04L41/22 , H04L41/046 , H04L41/0806 , H04L41/0879
摘要： The present invention generally relates to intelligent software agents. Each agent has an associated user interface panel through which the agent may be configured/customized. A remotely located user desiring to configure a particular agent issues a request for the associated user interface panel. The user interface panel may be provided to the user via, for example, a network connection. The user may then make the desired changes to the agent via the user interface panel. In this way, remote configuration of an agent is possible.
摘要翻译：本发明一般涉及智能软件代理。每个代理都有一个关联的用户界面面板，通过它可以配置/定制代理。希望配置特定代理的远程用户向相关联的用户界面面板发出请求。可以通过例如网络连接将用户界面面板提供给用户。然后，用户可以经由用户界面面板对代理进行所需的改变。以这种方式，可以远程配置代理。

2. 发明授权

US07721218B2 Mechanism for intelligent user interface presentation of a software agent 有权
标题翻译：智能用户界面呈现软件代理机制
公开(公告)号：US07721218B2
公开(公告)日：2010-05-18
申请号：US10403893
申请日：2003-03-31
申请人： Jeffrey T. Awe , Joseph P. Bigus , Anthony M. Dunbar , Gregory R. Hintermeister , Jacob Kugel , Donald A. Schlosnagle
发明人： Jeffrey T. Awe , Joseph P. Bigus , Anthony M. Dunbar , Gregory R. Hintermeister , Jacob Kugel , Donald A. Schlosnagle
IPC分类号： G06F3/00 , G06F9/00 , G06F17/00
CPC分类号： G06F9/451 , H04L67/10 , H04L67/36 , H04L69/329
摘要： The present invention generally relates to intelligent software agents. Agents are interfaced with through user interfaces that are generated according to the agent's intelligence. In one aspect, the interfaces are dynamically and programmatically generated in response to a request from a user desiring to interface with a particular agent. In this way, the interface may be generated in real time according to the applied intelligence of the agent. Interfaces may also be updated periodically and, in this way, be available prior to a user's request.
摘要翻译：本发明一般涉及智能软件代理。代理通过根据代理人的智能生成的用户界面来连接。在一个方面，响应于来自希望与特定代理接口的用户的请求动态地和编程地生成接口。以这种方式，可以根据代理的应用智能实时生成接口。接口也可以周期性地更新，并且以这种方式在用户请求之前可用。

3. 发明申请

US20050177792A1 Remote configuration of intelligent software agents 失效
标题翻译：智能软件代理的远程配置
公开(公告)号：US20050177792A1
公开(公告)日：2005-08-11
申请号：US10403950
申请日：2003-03-31
申请人： Jeffrey T. Awe , Joseph P. Bigus , Anthony M. Dunbar , Gregory R. Hintermeister , Jacob Kugel , Donald A. Schlosnagle
发明人： Jeffrey T. Awe , Joseph P. Bigus , Anthony M. Dunbar , Gregory R. Hintermeister , Jacob Kugel , Donald A. Schlosnagle
IPC分类号： G09G5/00 , H04L12/24
CPC分类号： H04L41/22 , H04L41/046 , H04L41/0806 , H04L41/0879
摘要： The present invention generally relates to intelligent software agents. Each agent has an associated user interface panel through which the agent may be configured/customized. A remotely located user desiring to configure a particular agent issues a request for the associated user interface panel. The user interface panel may be provided to the user via, for example, a network connection. The user may then make the desired changes to the agent via the user interface panel. In this way, remote configuration of an agent is possible.
摘要翻译：本发明一般涉及智能软件代理。每个代理都有一个关联的用户界面面板，通过它可以配置/定制代理。希望配置特定代理的远程用户向相关联的用户界面面板发出请求。可以通过例如网络连接将用户界面面板提供给用户。然后，用户可以经由用户界面面板对代理进行所需的改变。以这种方式，可以远程配置代理。

4. 发明授权

US07124119B2 Communication between intelligent agents and humans in a distributed system environment 有权
标题翻译：在分布式系统环境中智能代理和人员之间的通信
公开(公告)号：US07124119B2
公开(公告)日：2006-10-17
申请号：US10403649
申请日：2003-03-31
申请人： Joseph P. Bigus , Anthony M. Dunbar , Gregory R. Hintermeister
发明人： Joseph P. Bigus , Anthony M. Dunbar , Gregory R. Hintermeister
IPC分类号： G06F15/00
CPC分类号： G06Q10/06
摘要： A method, apparatus and article of manufacture for problem identification and resolution using intelligent agents. In at least one embodiment, an agent is a software element configured to detect a situation (e.g., problem or problems) and take steps to preserve a context in which the situation occurs. The agent may also be configured to identify one or more courses of action (e.g., solutions) to be taken in response to the situation. In one embodiment, a user trains an agent to take a particular action upon detecting a particular problem. The training may be initiated after accessing a log containing details about the problem context and recommended courses of action.
摘要翻译：使用智能代理进行问题识别和解决的方法，装置和制造。在至少一个实施例中，代理是被配置为检测情况（例如，问题或问题）的软件元件，并且采取措施来保留出现情况的上下文。代理还可以被配置为识别响应于该情况而采取的一个或多个动作行为（例如，解决方案）。在一个实施例中，用户训练代理以在检测到特定问题时采取特定动作。可以在访问包含有关问题背景和建议的行动方案的详细信息的日志之后启动培训。

5. 发明授权

US08214364B2 Modeling user access to computer resources 有权
标题翻译：建模用户对计算机资源的访问
公开(公告)号：US08214364B2
公开(公告)日：2012-07-03
申请号：US12124274
申请日：2008-05-21
申请人： Joseph P. Bigus , Leon Gong , Christoph Lingenfelder
发明人： Joseph P. Bigus , Leon Gong , Christoph Lingenfelder
IPC分类号： G06F17/30
CPC分类号： G06F21/552 , G06F21/316
摘要： Embodiments of the invention provide a method for detecting changes in behavior of authorized users of computer resources and reporting the detected changes to the relevant individuals. The method includes evaluating actions performed by each user against user behavioral models and business rules. As a result of the analysis, a subset of users may be identified and reported as having unusual or suspicious behavior. In response, the management may provide feedback indicating that the user behavior is due to the normal expected business needs or that the behavior warrants further review. The management feedback is available for use by machine learning algorithms to improve the analysis of user actions over time. Consequently, investigation of user actions regarding computer resources is facilitated and data loss is prevented more efficiently relative to the prior art approaches with only minimal disruption to the ongoing business processes.
摘要翻译：本发明的实施例提供了一种用于检测计算机资源的授权用户的行为变化并将检测到的变化报告给相关个人的方法。该方法包括评估每个用户针对用户行为模型和业务规则执行的动作。作为分析的结果，可以识别和报告用户的一部分具有不寻常或可疑行为。作为回应，管理层可以提供反馈意见，指出用户行为是由于正常的预期业务需求或行为值得进一步审查。管理反馈可供机器学习算法使用，以改善用户随时间的行为分析。因此，相对于现有技术方法，对于计算机资源的用户行为的调查被有助于更有效地防止数据丢失，而对正在进行的业务流程的中断只是最小的。

6. 发明申请

US20090292743A1 MODELING USER ACCESS TO COMPUTER RESOURCES 有权
标题翻译：建模用户访问计算机资源
公开(公告)号：US20090292743A1
公开(公告)日：2009-11-26
申请号：US12124274
申请日：2008-05-21
申请人： Joseph P. Bigus , Leon Gong , Christoph Lingenfelder
发明人： Joseph P. Bigus , Leon Gong , Christoph Lingenfelder
IPC分类号： G06F12/00
CPC分类号： G06F21/552 , G06F21/316
摘要： Embodiments of the invention provide a method for detecting changes in behavior of authorized users of computer resources and reporting the detected changes to the relevant individuals. The method includes evaluating actions performed by each user against user behavioral models and business rules. As a result of the analysis, a subset of users may be identified and reported as having unusual or suspicious behavior. In response, the management may provide feedback indicating that the user behavior is due to the normal expected business needs or that the behavior warrants further review. The management feedback is available for use by machine learning algorithms to improve the analysis of user actions over time. Consequently, investigation of user actions regarding computer resources is facilitated and data loss is prevented more efficiently relative to the prior art approaches with only minimal disruption to the ongoing business processes.
摘要翻译：本发明的实施例提供了一种用于检测计算机资源的授权用户的行为变化并将检测到的变化报告给相关个人的方法。该方法包括评估每个用户针对用户行为模型和业务规则执行的动作。作为分析的结果，可以识别和报告用户的一部分具有不寻常或可疑行为。作为回应，管理层可以提供反馈意见，指出用户行为是由于正常的预期业务需求或行为值得进一步审查。管理反馈可供机器学习算法使用，以改善用户随时间的行为分析。因此，相对于现有技术方法，对于计算机资源的用户行为的调查被有助于更有效地防止数据丢失，而对正在进行的业务流程的中断只是最小的。

7. 发明授权

US5617511A Neural network shell for application programs 失效
公开(公告)号：US5617511A
公开(公告)日：1997-04-01
申请号：US459858
申请日：1995-06-02
申请人： Joseph P. Bigus
发明人： Joseph P. Bigus
IPC分类号： G06N3/04 , G06F15/18
CPC分类号： G06N3/04
摘要： A neural network shell has a defined interface to an application program. By interfacing with the neural network shell, any application program becomes a neural network application program. The neural network shell contains a set of utility programs that transfers data into and out of a neural network data structure. This set of utility programs allows an application program to define a new neural network model, create a neural network data structure, train a neural network, and run a neural network. Once trained, the neural network data structure can be transported to other computer systems or to application programs written in different computing languages running on similar or different computer systems.

8. 发明授权

US5613043A Neural network shell for application programs 失效
公开(公告)号：US5613043A
公开(公告)日：1997-03-18
申请号：US459213
申请日：1995-06-02
申请人： Joseph P. Bigus
发明人： Joseph P. Bigus
IPC分类号： G06N3/04 , G06F15/18
CPC分类号： G06N3/04
摘要： A neural network shell has a defined interface to an application program. By interfacing with the neural network shell, any application program becomes a neural network application program. The neural network shell contains a set of utility programs that transfers data into and out of a neural network data structure. This set of utility programs allows an application program to define a new neural network model, create a neural network data structure, train a neural network, and run a neural network. Once trained, the neural network data structure can be transported to other computer systems or to application programs written in different computing languages running on similar or different computer systems.

9. 发明授权

US5615307A Neural network shell for application programs 失效
公开(公告)号：US5615307A
公开(公告)日：1997-03-25
申请号：US460361
申请日：1995-06-02
申请人： Joseph P. Bigus
发明人： Joseph P. Bigus
IPC分类号： G06N3/04 , G06F15/18
CPC分类号： G06N3/04
摘要： A neural network shell has a defined interface to an application program. By interfacing with the neural network shell, any application program becomes a neural network application program. The neural network shell contains a set of utility programs that transfers data into and out of a neural network data structure. This set of utility programs allows an application program to define a new neural network model, create a neural network data structure, train a neural network, and run a neural network. Once trained, the neural network data structure can be transported to other computer systems or to application programs written in different computing languages running on similar or different computer systems.

10. 发明授权

US5442730A Adaptive job scheduling using neural network priority functions 失效
标题翻译：使用神经网络优先级函数的自适应作业调度
公开(公告)号：US5442730A
公开(公告)日：1995-08-15
申请号：US134764
申请日：1993-10-08
申请人： Joseph P. Bigus
发明人： Joseph P. Bigus
IPC分类号： G06G7/60 , G06F9/46 , G06F9/48 , G06F9/50 , G06F15/18
CPC分类号： G06F9/4881
摘要： A job scheduler makes decisions concerning the order and frequency of access to a resource according to a substantially optimum delay cost function. The delay cost function is a single value function of one or more inputs, where at least one of the inputs is a delay time which increases as a job waits for service. The job scheduler is preferably used by a multi-user computer operating system to schedule jobs of different classes. The delay cost functions are preferably implemented by neural networks. The user specifies desired performance objectives for each job class. The computer system runs for a specified period of time, collecting data on system performance. The differences between the actual and desired performance objectives are computed, and used to adaptively train the neural network. The process repeats until the delay cost functions stabilize near optimum value. However, if the system configuration, workload, or desired performance objectives change, the neural network will again start to adapt.
摘要翻译：作业调度器根据基本上最佳的延迟成本函数做出关于资源访问顺序和频率的决定。延迟成本函数是一个或多个输入的单值函数，其中至少一个输入是随着作业等待服务而增加的延迟时间。作业调度程序优选地由多用户计算机操作系统使用以调度不同类别的作业。延迟成本函数优选地由神经网络实现。用户为每个作业类别指定所需的性能目标。计算机系统运行指定的时间段，收集有关系统性能的数据。计算实际和期望性能目标之间的差异，并用于自适应训练神经网络。该过程重复，直到延迟成本函数稳定在最佳值附近。然而，如果系统配置，工作负载或期望的性能目标改变，神经网络将再次开始适应。

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