Knowledge acquisition in different cognitive architectures and knowledge-based systems is mainly performed by manually inserted knowledge, as well as by learning from new situations, revealed from current knowledge base. In RGT Solvers of combinatorial games, knowledge is acquired hand to hand with experts and by revelation. Earlier, certain procedures of acquiring and explaining strategy RGT knowledge were outlined. This work aimed to implement these procedures, thus, to advance in automating human-computer communications.

Topics
Learning and learning models, Knowledge
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