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This paper applies a genetic algorithm and fuzzy markup language to constructa human and smart machine cooperative learning system on game of Go. Thegenetic fuzzy markup language (GFML)-based Robot Agent can work on variouskinds of robots, including Palro, Pepper, and TMUs robots. We use theparameters of FAIR open source Darkforest and OpenGo AI bots to construct theknowledge base of Open Go Darkforest (OGD) cloud platform for student learningon the Internet. In addition, we adopt the data from AlphaGo Master sixtyonline games as the training data to construct the knowledge base and rule baseof the co-learning system. First, the Darkforest predicts the win rate based onvarious simulation numbers and matching rates for each game on OGD platform,then the win rate of OpenGo is as the final desired output. The experimentalresults show that the proposed approach can improve knowledge base and rulebase of the prediction ability based on Darkforest and OpenGo AI bot withvarious simulation numbers.

A GFML-based Robot Agent for Human and Machine Cooperative Learning on Game of Go