| Technical Name | Applying CGI Go Programs to Go Tutoring | ||
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| Project Operator | National Chiao Tung University | ||
| Project Host | 吳毅成 | ||
| Summary | DeepMind successfully developed AlphaGo, a Go program, beating top human players. However, the current Go programs based on AlphaGo still cannot be used in Go Tutoring, e.g., life-and-death problems, block connections, global board evaluations. In this technique, we solve these problems for tutoring based on CGI programs, developed by our group in the past. |
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| Scientific Breakthrough | Although the current AlphaGo-like programs can surpass top human players, they still cannot exactly provesolve some common tutoring problems well, like life-and-death (L&D) questions. Here, we propose to combine deep reinforcement learningrelevance zone techniques to solve L&D problems. |
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| Industrial Applicability | (Provided later) |
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| Keyword | Deep Learning Reinforcement Learning Deep Reinforcement Learning Neural Network Multi-Labelled Value Network Artificial Intelligence Relevance-Zone Board Evaluation AlphaGo Zero Alpha Zero | ||
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