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($lambda$) learning to test the performance. The experimental result reveals that even the simple neuro-fuzzy reasoning model can compete against TD($lambda$) learning and it shows great potential to be applied to the real game of Go.