Projections and symmetric expansions of a learning space
Jean‐Claude Falmagne · arXiv (Cornell University) · 2008
Any subset Q ′ of the domain Q of a learning space K defines a projection of K on Q ′ which is itself a learning space consistent with K. Moreover, such a construction defines a partition of Q having each of its classes defining a learning space also consistent with K. We give a direct proof of these facts which are instrumental in parsing large learning spaces. We also develop, in a highly symmetric case, the reverse concept of an ‘expansion’ of a learning space, an operation capable of iteration.