1. Blythe, J. & Veloso, M. M. (in press). Analogical Replay for Efficient Conditional Planning. To appear in the Proceedings of the Fourteenth National Conference on Artificial Intelligence. Menlo Park, CA: AAAI Press.
2. Blythe, J., Veloso, M. M., & de Souza, L. (1997). The Prodigy user interface (Tech. Rep. No. CMU-CS-97-114). Carnegie Mellon University, Computer Science Dept.
3. Carbonell, J. G. (1986), Derivational analogy: A theory of reconstructive problem solving and expertise acquisition. In R. Michalski, J. Carbonell & T. Mitchell (Eds.), Machine learning: An artificial intelligence approach, Vol. 2 (pp. 371–392). San Mateo, CA: Morgan Kaufmann.
4. Cox, M. T., & Veloso, M. M. (1997). Controlling for unexpected goals when planning in a mixed-initiative setting. Submitted.
5. Ferguson, G., Allen, J. F., & Miller, B. (1996). TRAINS-95: Towards a mixed-initiative planning assistant. In Proceedings of the Third International Conference on AI Planning Systems (AIPS-96), Edinburgh, Scotland, May 29–31,1996.