Invention Grant
- Patent Title: Weight initialization for random neural network reinforcement learning
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Application No.: US15718901Application Date: 2017-09-28
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Publication No.: US10257072B1Publication Date: 2019-04-09
- Inventor: Samer Salam
- Applicant: Cisco Technology, Inc.
- Applicant Address: US CA San Jose
- Assignee: Cisco Technology, Inc.
- Current Assignee: Cisco Technology, Inc.
- Current Assignee Address: US CA San Jose
- Agency: Edell, Shapiro & Finnan, LLC
- Main IPC: H04L12/751
- IPC: H04L12/751 ; G06N3/04 ; G06N3/08

Abstract:
A plurality of paths through a network are determined for transmitting a packet from a source device to a destination device. The paths are modelled as nodes in a Random Neural Network, each node corresponding to a path and a reward is calculated for each of the nodes. An excitatory weight and an inhibitory weight are determined for each of the nodes in the Random Neural Network. The excitatory weight is set directly proportional to the reward corresponding to the node for which the excitatory weight is being determined, and the inhibitory weight is set inversely proportional to the reward corresponding to the node for which the inhibitory weight is being determined. A potential is determined for each of the nodes based upon the excitatory and inhibitory weights. A path corresponding to the node with the highest potential is selected, and the packet is transmitted over the selected path.
Public/Granted literature
- US20190097912A1 WEIGHT INITIALIZATION FOR RANDOM NEURAL NETWORK REINFORCEMENT LEARNING Public/Granted day:2019-03-28
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