论文信息 - Human and Smart Machine Co-Learning with Brain Computer Interface

Human and Smart Machine Co-Learning with Brain Computer Interface

Machine learning has become a very popular approach for cybernetics systems, and it has always been considered important research in the Computational Intelligence area. Nevertheless, when it comes to smart machines, it is not just about the methodologies. We need to consider systems and cybernetics as well as include human in the loop. The purpose of this article is as follows: (1) To integrate the open source Facebook AI Research (FAIR) DarkForest program of Facebook with Item Response Theory (IRT), to the new open learning system, namely, DDF learning system; (2) To integrate DDF Go with Robot namely Robotic DDF Go system; (3) To invite the professional Go players to attend the activity to play Go games on site with a smart machine. The research team will apply this technology to education, such as, playing games to enhance the children concentration on learning mathematics, languages, and other topics. With the detected brainwaves, the robot will be able to speak some words that are very much to the point for the students and to assist the teachers in classroom in the future.

[1] Shang-Lin Wu,et al. EEG-Based Brain-Computer Interfaces: A Novel Neurotechnology and Computational Intelligence Method , 2017, IEEE Systems, Man, and Cybernetics Magazine.

[2] I-Chen Wu,et al. Human vs. Computer Go: Review and Prospect , 2016, ArXiv.

[3] Olivier Teytaud,et al. T2FS-Based Adaptive Linguistic Assessment System for Semantic Analysis and Human Performance Evaluation on Game of Go , 2015, IEEE Transactions on Fuzzy Systems.

[4] Tzung-Pei Hong,et al. The Computational Intelligence of MoGo Revealed in Taiwan's Computer Go Tournaments , 2009, IEEE Transactions on Computational Intelligence and AI in Games.

[5] Yuandong Tian,et al. Better Computer Go Player with Neural Network and Long-term Prediction , 2016, ICLR.

[6] A.P. Vinod,et al. Toward EEG-Based Biometric Systems: The Great Potential of Brain-Wave-Based Biometrics , 2017, IEEE Systems, Man, and Cybernetics Magazine.

[7] Demis Hassabis,et al. Mastering the game of Go without human knowledge , 2017, Nature.

[8] Naoyuki Kubota,et al. FML-based Dynamic Assessment Agent for Human-Machine Cooperative System on Game of Go , 2017, Int. J. Uncertain. Fuzziness Knowl. Based Syst..