Chang-Shing Lee

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Chang-Shing Lee, a Taiwanese computer scientist and professor at National University of Tainan (NUTN). His major research interests are in ontology applications, knowledge management, capability maturity model integration (CMMI), semantic web, and artificial intelligence. He is also interested in intelligent agent, web services, fuzzy logic, genetic algorithm, and image processing. Chang-Shing Lee holds several patents on ontology engineering, document classificaton, image filtering and health care.

=MogoTW= Chang-Shing Lee is co-programmer of the Go playing program MogoTW , a joint project between the MoGo team and a Taiwanese team. It shares code with MoGo.

=FML-based Prediction= Abtract from FML-based Prediction Agent and Its Application to Game of Go : In this paper, we present a robotic prediction agent including a darkforest Go engine, a fuzzy markup language (FML) assessment engine, an FML-based decision support engine, and a robot engine for game of Go application. The knowledge base and rule base of FML assessment engine are constructed by referring the information from the darkforest Go engine located in NUTN and OPU, for example, the number of MCTS simulations and winning rate prediction. The proposed robotic prediction agent first retrieves the database of Go competition website, and then the FML assessment engine infers the winning possibility based on the information generated by darkforest Go engine. The FML-based decision support engine computes the winning possibility based on the partial game situation inferred by FML assessment engine. Finally, the robot engine combines with the human-friendly robot partner PALRO, produced by FujiSoft Incorporated, to report the game situation to human Go players. Experimental results show that the FML-based prediction agent can work effectively.

=PFML-based BCI Agent= Abtract from PFML-based Semantic BCI Agent for Game of Go Learning and Prediction : This paper presents a semantic brain computer interface (BCI) agent with particle swarm optimization (PSO) based on a Fuzzy Markup Language (FML) for Go learning and prediction applications. Additionally, we also establish an Open Go Darkforest (OGD) cloud platform with Facebook AI research (FAIR) open source Darkforest and ELF OpenGo AI bots. The Japanese robot Palro will simultaneously predict the move advantage in the board game Go to the Go players for reference or learning. The proposed semantic BCI agent operates efficiently by the human-based BCI data from their brain waves and machine-based game data from the prediction of the OGD cloud platform for optimizing the parameters between humans and machines. Experimental results show that the proposed human and smart machine co-learning mechanism performs favorably. We hope to provide students with a better online learning environment, combining different kinds of handheld devices, robots, or computer equipment, to achieve a desired and intellectual learning goal in the future.

=Selected Publications=

2007 ...

 * Chang-Shing Lee, Mei-Hui Wang (2007). Ontology-based intelligent healthcare agent and its application to respiratory waveform recognition. Expert Systems with Applications, Vol. 33, No. 3
 * Guillaume Chaslot, Jean-Baptiste Hoock, Arpad Rimmel, Olivier Teytaud, Chang-Shing Lee, Mei-Hui Wang, Shang-Rong Tsai, Shun-Chin Hsu (2008). Human-Computer Go Revolution 2008. ICGA Journal, Vol. 31, No. 3
 * Chang-Shing Lee, Mei-Hui Wang, Yuan-Liang Wang, Shun-Chin Hsu (2008). The 2008 computational intelligence forum and the world 9x9 computer-Go championship in Taiwan. ICGA Journal, Vol. 31, No. 4
 * Chang-Shing Lee, Mei-Hui Wang, Guillaume Chaslot, Jean-Baptiste Hoock, Arpad Rimmel, Olivier Teytaud, Shang-Rong Tsai, Shun-Chin Hsu, Tzung-Pei Hong (2009). The Computational Intelligence of MoGo Revealed in Taiwan's Computer Go Tournaments. IEEE Transactions on Computational Intelligence and AI in Games, pdf
 * Chang-Shing Lee, Mei-Hui Wang, Tzung-Pei Hong, Guillaume Chaslot, Jean-Baptiste Hoock, Arpad Rimmel, Olivier Teytaud, Yau-Hwang Kuo (2009). A Novel Ontology for Computer Go Knowledge Management. IEEE FUZZ, pdf

2010 ...

 * Chang-Shing Lee, Mei-Hui Wang, Shi-Jim Yen, Yu-Jen Chen, Cheng-Wei Chou, Guillaume Chaslot, Jean-Baptiste Hoock, Arpad Rimmel, Hassen Doghmen (2010). An ontology-based fuzzy inference system for computer Go applications. International Journal of Fuzzy Systems, Vol. 12, No. 2, pdf
 * Jean-Baptiste Hoock, Chang-Shing Lee, Arpad Rimmel, Fabien Teytaud, Mei-Hui Wang, Olivier Teytaud (2010). Intelligent Agents for the Game of Go. IEEE Computational Intelligence Magazine, Vol. 5, pdf
 * Arpad Rimmel, Olivier Teytaud, Chang-Shing Lee, Shi-Jim Yen, Mei-Hui Wang, Shang-Rong Tsai (2010). Current Frontiers in Computer Go. IEEE Transactions on Computational Intelligence and AI in Games, Vol. 2
 * Cheng-Wei Chou, Ping-Chiang Chou, Hassen Doghmen, Chang-Shing Lee, Tsan-Cheng Su, Fabien Teytaud, Olivier Teytaud, Hui-Ming Wang, Mei-Hui Wang, Li-Wen Wu, Shi-Jim Yen (2011). Towards a Solution of 7x7 Go with Meta-MCTS. Advances in Computer Games 13
 * Chang-Shing Lee, Mei-Hui Wang, Olivier Teytaud, Shi-Jim Yen (2012). Human vs. Machine Go Competitions in IEEE WCCI 2012. ICGA Journal, Vol. 35, No. 4
 * Ping-Chiang Chou, Shi-Jim Yen, Cheng-Wei Chou, Ching-Nung Lin, Chang-Shing Lee, Olivier Teytaud, Hassen Doghmen (2012). A simple Tsumego Generator. GPW 2012
 * Cheng-Wei Chou, Ping-Chiang Chou, Chang-Shing Lee, David L. Saint-Pierre, Olivier Teytaud, Mei-Hui Wang, Li-Wen Wu, Shi-Jim Yen (2012). Strategic Choices: Small Budgets and Simple Regret. TAAI 2012, Excellent Paper Award, pdf
 * Giovanni Acampora, Vincenzo Loia, Chang-Shing Lee, Mei-Hui Wang (eds.) (2013). On the Power of Fuzzy Markup Language. Studies in Fuzziness and Soft Computing, Vol. 296, Springer
 * Chang-Shing Lee, Mei-Hui Wang, Yu-Jen Chen, Shi-Jim Yen (2013). Apply Fuzzy Markup Language to Knowledge Representation for Game of Computer Go.


 * Ting-Han Wei, I-Chen Wu, Chao-Chin Liang, Bing-Tsung Chiang, Wen-Jie Tseng, Shi-Jim Yen, Chang-Shing Lee (2014). Job-Level Algorithms for Connect6 Opening Position Analysis. ECAI CGW 2014

2015 ...

 * Ting-Han Wei, I-Chen Wu, Chao-Chin Liang, Bing-Tsung Chiang, Wen-Jie Tseng, Shi-Jim Yen, Chang-Shing Lee (2015). Job-Level Algorithms for Connect6 Opening Book Construction. ICGA Journal, Vol. 38, No. 3
 * Chang-Shing Lee, Mei-Hui Wang, Shi-Jim Yen, Ting-Han Wei, I-Chen Wu, Ping-Chiang Chou, Chun-Hsun Chou, Ming-Wan Wang, Tai-Hsiung Yang (2016). Human vs. Computer Go: Review and Prospect. arXiv:1606.02032
 * Chang-Shing Lee, Mei-Hui Wang, Chia-Hsiu Kao, Sheng-Chi Yang, Yusuke Nojima, Ryosuke Saga, Nan Shuo, Naoyuki Kubota (2017). FML-based Prediction Agent and Its Application to Game of Go. arXiv:1704.04719
 * Chang-Shing Lee, Mei-Hui Wang, Sheng-Chi Yang, Pi-Hsia Hung, Su-Wei Lin, Nan Shuo, Naoyuki Kubota, Chun-Hsun Chou, Ping-Chiang Chou, Chia-Hsiu Kao (2017). FML-based Dynamic Assessment Agent for Human-Machine Cooperative System on Game of Go. arXiv:1707.04828
 * Chang-Shing Lee, Mei-Hui Wang, Li-Wei Ko, Naoyuki Kubota, Lu-An Lin, Shinya Kitaoka, Yu-Te Wang, Shun-Feng Su (2018). Human and Smart Machine Co-Learning with Brain Computer Interface. arXiv:1802.06521
 * Chang-Shing Lee, Mei-Hui Wang, Li-Wei Ko, Bo-Yu Tsai, Yi-Lin Tsai, Sheng-Chi Yang, Lu-An Lin, Yi-Hsiu Lee, Hirofumi Ohashi, Naoyuki Kubota, Nan Shuo (2019). PFML-based Semantic BCI Agent for Game of Go Learning and Prediction. arXiv:1901.02999
 * Chang-Shing Lee, Mei-Hui Wang, Li-Chuang Chen, Yusuke Nojima, Tzong-Xiang Huang, Jinseok Woo, Naoyuki Kubota, Eri Sato-Shimokawara, Toru Yamaguchi (2019). A GFML-based Robot Agent for Human and Machine Cooperative Learning on Game of Go. arXiv:1901.07191

=External Links=
 * Chang-Shing Lee | Ph. D. | National University of Tainan
 * Lee, Chang-Shing from computer-go.info
 * Chang-Shing Lee | Facebook

=References= Up one level