Applying Neuro-fuzzy Reasoning to Go Opening Games
Byung-Doo Lee · Journal of Korea Game Society · 2009
This paper describes the result of applying neuro-fuzzy reasoning, which conducts Go term knowledge based on pattern knowledge, to the opening game of Go. We discuss the implementation of neuro-fuzzy reasoning for deciding the best next move to proceed through the opening game. We also let neuro-fuzzy reasoning play against TD() learning to test the performance. The experimental result reveals that even the simple neuro-fuzzy reasoning model can compete against TD() learning and it shows great potential to be applied to the real game of Go.