Quantum evolutionary algorithm with connectionist learning

A quantized and quantum technology, applied in the field of quantum evolutionary algorithms with connection learning, can solve problems such as limiting the application range of univariate distribution estimation algorithms and not being able to handle them, so as to improve efficiency and avoid computing resources

Inactive Publication Date: 2016-04-13
TSINGHUA UNIV
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  • Description
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AI Technical Summary

Problems solved by technology

[0010] The univariate distribution estimation algorithm is simple and efficient, but the variables of the probability vector are independent of each other s

Method used

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  • Quantum evolutionary algorithm with connectionist learning
  • Quantum evolutionary algorithm with connectionist learning
  • Quantum evolutionary algorithm with connectionist learning

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Embodiment Construction

[0021] The present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.

[0022] Such as figure 1 As shown, the present invention provides a kind of quantum evolutionary algorithm with connection learning, and this algorithm is made of several computing units, and each computing unit all comprises quantum individual (QuantumIndividual) Q i , Collapsed Individual (CollapsedIndividual) C i and Attractor A i , where i represents the serial number of the calculation unit, i=1, 2, ..., N, where N is a natural number. The steps of the present invention are as follows:

[0023] 1) Initialize the quantum individual Q in all computing units i , the quantum individual Q i medium qubit with initialized to That is, all quantized individuals are initialized to the same value; where i represents the serial number of the computing unit, that is, the i-th quantum individual; j represents the position of the j-th gene.

[0024]...

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Abstract

The invention relates to a quantum evolutionary algorithm with connectionist learning, which is composed of a plurality of calculation units, and each calculation unit comprises a quantum individual, a collapsing individual and an attractor; the steps are as follows: initializing quantum individuals in all calculation units; for the ith calculation unit, directly sampling the quantum individual and a concept guide combination operator, and obtaining the collapsing individual, and using an objective function to evaluate the collapsing individual to obtain an adaptive value; evaluating the attractor into a corresponding collapsing individual according to the collapsing individual, and finishing initialization of the calculation units; initializing an information metric matrix formed by information quantity of the quantum individual into a 0 matrix; using a collapsing state generation algorithm to generate the collapsing individual by the quantum individual, and generating a temporary probability vector by partial collapsing individuals, and directly sampling corresponding quantum individuals by other collapsing individuals; updating quantum individuals and attractors in all calculation units according to adaptive values of the attractors and adaptive values of the collapsing individuals; and when reaching preset maximum number of iterations, then the quantum evolution process is finished.

Description

technical field [0001] The invention relates to a quantum evolutionary algorithm, in particular to a quantum evolutionary algorithm with connection learning. Background technique [0002] Quantum evolutionary algorithm (QEA) only uses some concepts of quantum computing, and its essence is a multi-model evolutionary algorithm running on a classical computer, including qubits, quantum entities, quantum gates, and collapsed entities. Compared with the traditional evolutionary algorithm, the main feature of QEA is that the basic unit of storing information is different. The basic unit of the traditional evolutionary algorithm is a bit, and a bit can only be in a state of either 0 or 1. The concept of quantum computing is borrowed in the QEA algorithm, which uses qubits as the basic information unit. In the process of quantum computing, a qubit is in a superposition state, that is, it is in different eigenstates at the same time. It just collapses to an eigenstate when observe...

Claims

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Application Information

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IPC IPC(8): G06N3/12
CPCG06N3/126
Inventor 徐华
Owner TSINGHUA UNIV
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