APPARATUS AND METHODS FOR DEVELOPING PARALLEL NETWORKS USING A GENERAL PURPOSE PROGRAMMING LANGUAGE
    1.
    发明申请
    APPARATUS AND METHODS FOR DEVELOPING PARALLEL NETWORKS USING A GENERAL PURPOSE PROGRAMMING LANGUAGE 有权
    使用一般用途编程语言开发并行网络的装置和方法

    公开(公告)号:US20160217370A1

    公开(公告)日:2016-07-28

    申请号:US15090487

    申请日:2016-04-04

    CPC classification number: G06N3/105 G06N3/049

    Abstract: Apparatus and methods for developing parallel networks. Parallel network design may comprise a general purpose language (GPC) code portion and a network description (ND) portion. GPL tools may be utilized in designing the network. The GPL tools may be configured to produce network specification language (NSL) engine adapted to generate hardware optimized machine executable code corresponding to the network description. The developer may be enabled to describe a parameter of the network. The GPC portion may be automatically updated consistent with the network parameter value. The GPC byte code may be introspected by the NSL engine to provide the underlying source code that may be automatically reinterpreted to produce the hardware optimized machine code. The optimized machine code may be executed in parallel.

    Abstract translation: 用于开发并行网络的装置和方法。 并行网络设计可以包括通用语言(GPC)代码部分和网络描述(ND)部分。 GPL工具可用于设计网络。 GPL工具可以被配置为产生适于生成对应于网络描述的硬件优化机器可执行代码的网络规范语言(NSL)引擎。 可以使开发人员能够描述网络的参数。 可以根据网络参数值自动更新GPC部分。 GPC字节码可以由NSL引擎内省,以提供可以自动重新解释以产生硬件优化机器代码的底层源代码。 优化的机器代码可以并行执行。

    INTELLIGENT MODULAR ROBOTIC APPARATUS AND METHODS
    2.
    发明申请
    INTELLIGENT MODULAR ROBOTIC APPARATUS AND METHODS 有权
    智能模块化机器人和方法

    公开(公告)号:US20150324687A1

    公开(公告)日:2015-11-12

    申请号:US14468928

    申请日:2014-08-26

    CPC classification number: G06N3/04 G06N3/008 G06N3/02 G06N3/049 G06N3/063 G06N3/08

    Abstract: Apparatus and methods for an extensible robotic device with artificial intelligence and receptive to training controls. In one implementation, a modular robotic system that allows a user to fully select the architecture and capability set of their robotic device is disclosed. The user may add/remove modules as their respective functions are required/obviated. In addition, the artificial intelligence is based on a neuronal network (e.g., spiking neural network), and a behavioral control structure that allows a user to train a robotic device in manner conceptually similar to the mode in which one goes about training a domesticated animal such as a dog or cat (e.g., a positive/negative feedback training paradigm) is used. The trainable behavior control structure is based on the artificial neural network, which simulates the neural/synaptic activity of the brain of a living organism.

    Abstract translation: 具有人工智能和接受训练控制的可扩展机器人装置的装置和方法。 在一个实现中,公开了允许用户完全选择其机器人设备的架构和能力集合的模块化机器人系统。 用户可以添加/删除模块,因为它们各自的功能是必需/免除的。 另外,人工智能是基于神经元网络(例如,刺激神经网络)以及行为控制结构,其允许用户以概念上类似于关于训练驯养动物的模式来训练机器人装置 例如狗或猫(例如,正/负反馈训练范例)。 可训练行为控制结构基于人造神经网络,其模拟活体的脑的神经/突触活动。

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