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Server-free computing resource allocation method based on maximum entropy inverse reinforcement learning

A reinforcement learning and serverless technology, which is applied in the field of serverless computing resource allocation, can solve problems such as resource waste and achieve the effect of maximizing benefits

Pending Publication Date: 2022-04-29
SHENZHEN INST OF ADVANCED TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, on the one hand, it causes a serious waste of resources; on the other hand, it creates unnecessary learning costs and time overhead for users.

Method used

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  • Server-free computing resource allocation method based on maximum entropy inverse reinforcement learning
  • Server-free computing resource allocation method based on maximum entropy inverse reinforcement learning
  • Server-free computing resource allocation method based on maximum entropy inverse reinforcement learning

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Embodiment Construction

[0022] In order to make the above objects, features and advantages of the present invention more comprehensible, specific implementations of the present invention will be described in detail below in conjunction with the accompanying drawings. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. However, the present invention can be implemented in many other ways different from those described here, and those skilled in the art can make similar improvements without departing from the connotation of the present invention, so the present invention is not limited by the specific embodiments disclosed below.

[0023] In describing the present invention, it should be understood that the terms "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", " Back", "Left", "Right", "Vertical", "Horizontal", "Top", "Bottom", "Inner", "Outer", "Clockwise", "Counte...

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PUM

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Abstract

The invention discloses a server-free computing resource allocation method, device and equipment based on maximum entropy inverse reinforcement learning and a storage medium thereof. The method comprises the steps that an intelligent agent randomly generates a preset strategy; comparing the data obtained by sampling the preset strategy with the data obtained by sampling the expert data, and learning a reward function; carrying out reinforcement learning by utilizing the learned reward function to obtain a reinforced self-strategy; and judging the difference of the own strategies, and stopping comparison when the difference of the own strategies is smaller than a threshold value. According to the scheme provided by the invention, after basic training is completed, the scheme is a completely online learning method, and the training is not needed. According to the invention, the parameters can be dynamically adjusted, and the space of price and income is fully explored, so that the benefits of the user and the platform are maximized.

Description

technical field [0001] The present invention relates to the technical field of computer architecture, in particular to a serverless computing resource configuration method, device, equipment and storage medium based on maximum entropy inverse reinforcement learning. Background technique [0002] Serverless computing refers to building and running applications without managing infrastructure such as servers. It describes a more fine-grained deployment model in which an application is broken down into one or more fine-grained functions that are uploaded to a platform and then executed, scaled and billed based on current needs. [0003] Serverless computing does not mean that servers are no longer used to host and run code, nor does it mean that operations engineers are no longer needed. Instead, consumers of serverless computing no longer need to perform server provisioning, maintenance, updates, scaling, and capacity planning. These tasks and functions are all handled by the...

Claims

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Application Information

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IPC IPC(8): G06F9/50G06N20/00
CPCG06F9/5027G06N20/00
Inventor 叶可江林彦颖须成忠
Owner SHENZHEN INST OF ADVANCED TECH
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