Proceedings of the Annual Conference of JSAI
Online ISSN : 2758-7347
34th (2020)
Session ID : 2M4-OS-3a-04
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Investigation of genetic algorithm for autonomous AI using blockchain
*Kanta NANRIYutaka MORIYAMAKoichi NAKAYAMA
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Abstract

This paper proposed ``Self-Administered Genetic Algorithm (SA-GA)'' as an evolutionary method that applies systems of intelligent autonomous agents. The intelligent autonomous agents were implemented as an autonomous program called a smart contract and executed by themselves according to pay the cryptocurrency to a node of the block chain. The intelligent autonomous agents' copies (children) were created by acquiring the cryptocurrency from their parents. In the examination of this paper, SA-GA was applied to a problem that resources which a large number of unspecified users provided were allocated to a large number of unspecified users. The result showed that SA-GA could obtain an adequate solution without a management for whole system. Moreover, it was shown that these solutions could be obtained in practical calculation time. Namely, SA-GA can be a method that optimizes the system consisting of a large number of autonomous agents.

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© 2020 The Japanese Society for Artificial Intelligence
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