Cluster behavior learning method based on gene programming

Abstract

The invention provides a cluster behavior learning method based on gene programming, which utilizes a gene programming method to carry out heuristic search on a solution space without priori knowledge, and finally gives a neighbor selection mechanism and a behavior decision function which can well reflect a cluster real motion rule. Under the trend that a forward modeling means is generally adopted at present, a new path is found to learn cluster individual motion rules by adopting an inversion mode. Cluster behavior rule learning under the priori knowledge-free condition is achieved, the vacancy of the learning method in the field can be filled up, and the method can be used for learning of unmanned cluster behaviors and can also be used for research of biological cluster behaviors.

Description

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AI Technical Summary

Benefits of technology

The purpose of this patented technology allows for an algorithm called Genetic Programming (GP) to find solutions within certain spaces efficiently while avoids previous data or assumptions about how clusters move around. This makes it possible to better predict future movements based solely on past ones rather than relying only upon previously-existing models.

Problems solved by technology

Technological Problem: Current methods used by groups involved in team work cannot predict how well their members behave when interact with each other without being able to talk about them effectively during training sessions.

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