Transfer Learning through Analogy in Games

We find that a major benefit of analogy is that it reduces the extent to which the source domain must be generalized before transfer. We describe two techniques in particular, minimal ascension and metamapping, that enable analogies to be drawn even when comparing descriptions using different relational vocabularies. Evidence for the effectiveness of these techniques is provided by a large-scale external evaluation, involving a substantial number of novel distant analogs. This is the objective of transfer learning, in which transferred knowledge guides the learning process in a broad range of new situations. In near transfer, the source and target domains are very similar and solutions can be transferred almost verbatim.