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We present a new general board game (GBG) playing and learning framework. GBGdefines the common interfaces for board games, game states and their AI agents.It allows one to run competitions of different agents on different games. Itstandardizes those parts of board game playing and learning that otherwisewould be tedious and repetitive parts in coding. GBG is suitable for arbitrary1-, 2-, ..., N-player board games. It makes a generic TD($\lambda$)-n-tupleagent for the first time available to arbitrary games. On various games,TD($\lambda$)-n-tuple is found to be superior to other generic agents likeMCTS. GBG aims at the educational perspective, where it helps students to startfaster in the area of game learning. GBG aims as well at the researchperspective by collecting a growing set of games and AI agents to assess theirstrengths and generalization capabilities in meaningful competitions. Initialsuccessful educational and research results are reported.

General Board Game Playing for Education and Research in Generic AI Game Learning