Rivest, F., & Shultz, T. R. (2004). Compositionality in a knowledge-based constructive learner. Papers from the 2004 AAAI Fall Symposium, Technical Report FS-04-03, pp. 54-58. AAAI Press: Menlo Park, CA.



A knowledge-based constructive learning algorithm, KBCC, simplifies and accelerates the learning of parity and chessboard problems. Previously learned knowledge of simpler versions of these problems is recruited in the service of learning more complex versions. A learned solution can be viewed as a composition in which the components are not altered, showing that concatenative compositionality can be achieved in neural terms.


Copyright notice

Abstracts, papers, chapters, and other documents are posted on this site as an efficient way to distribute reprints. The respective authors and publishers of these works retain all of the copyrights to this material. Anyone copying, downloading, bookmarking, or printing any of these materials agrees to comply with all of the copyright terms. Other than having an electronic or printed copy for fair personal use, none of these works may be reposted, reprinted, or redistributed without the explicit permission of the relevant copyright holders.


To obtain a PDF reprint of this particular article, signal your agreement with these copyright terms by clicking on the statement below.


I agree with all of these copyright terms PDF 177KB