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AssigneeHuawei Technologies Co., Ltd.
InventorsHengshuai Yao, Seyed Masoud Nosrati, Hao Chen, Peyman Yadmellat, Yunfei Zhang
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A method, device and system of prediction of a state of an object in the environment using an action model of a neural network. In accordance with one aspect, a control system for a object comprises a processor, a plurality of sensors coupled to the processor for sensing a current state of the object and an environment in which the object is located, and a first neural network coupled to the processor. One or more predicted subsequent states of the object in the environment are determined using an action model of the neural network and a current state of the object in the environment and an plurality of action sequences. The action model comprises a mapping of states of the object in the environment and actions performed by the object for each state to predicted subsequent states of the object in the environment.
A control system, comprising:
A method of selection of an action for an object using a neural network, the method comprising:
A non-transitory machine readable medium having tangibly stored thereon executable instructions for execution by a processor of a control system for an object, wherein the executable instructions, when executed by the processor, cause the control system to:
A method of learning an action model for an object in an environment using a neural network, the method comprising:
Dependencies are inferred from the claim text.