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Based on recently explored heuristic service composition methods

A service combination and heuristic technology, applied in digital transmission systems, data exchange networks, electrical components, etc., can solve the problem of low algorithm efficiency, and achieve the effect of speeding up learning and reducing blind exploration.

Active Publication Date: 2019-10-11
SOUTHEAST UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

When the agent has no knowledge of the environment at all, it has to learn by trial and error method, the algorithm is not efficient

Method used

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  • Based on recently explored heuristic service composition methods
  • Based on recently explored heuristic service composition methods
  • Based on recently explored heuristic service composition methods

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Embodiment Construction

[0042] The present invention will be further explained below in conjunction with the accompanying drawings and specific embodiments.

[0043]A method based on a recently explored heuristic service composition, including the following steps:

[0044] Step 1. Model the service composition problem as a six-tuple Markov decision process:

[0045] MDP-WSC=0 ;s r ;A(·);P;R>

[0046] where S represents the set of all states that can be experienced during the process of migrating from the initial state to the final state; s 0 is the initial state, indicating the state when any action has not occurred, s 0 ∈ S; s r is the terminal state, when the system reaches the final state, it indicates that a complete service execution path has been formed, and a complete combined service can be constructed, s r ∈S; A( ) represents the set of actions that the system can take in the state s∈S; P is the state transition function; R is the reward function.

[0047] Step 2. Apply the heuristic l...

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Abstract

The invention discloses a heuristic service composition method based on recent explorations, comprising the following steps: 1. Modeling the service composition problem as a six-tuple Markov decision process; 2. Applying Q-learning-based heuristic learning The method solves the six-tuple Markov decision process to obtain the optimal strategy; 3. Maps the optimal strategy to the workflow of web service composition. This method makes full use of the learning experience in the learning process to improve the learning speed, and the learning efficiency is higher.

Description

technical field [0001] The invention relates to a method for combining Web services by using a computer, which belongs to the field of artificial intelligence. Background technique [0002] As an implementation of Service-Oriented Architecture (SOA), Web service inherits the characteristics of SOA such as self-contained and self-describing, and can be invoked by applications through the Internet. Such as figure 1 As shown, the implementation process of a Web service: the service provider sends the service description information to the service registration center for registration, so that potential users can discover these services; the service requester searches for the Web service, writes the service description and binding information through UDDI Enter the registry; according to business requirements, the service requester searches the Web service through UDDI through the network, and locates the service provider according to the found binding information; the service r...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L29/08H04L12/24
CPCH04L41/142H04L67/02H04L67/51
Inventor 王红兵费欢欢
Owner SOUTHEAST UNIV
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