ד"ר עמי האופטמן

Hauptman, A., Balasubramaniam, G. M., & Arnon, S. (2023). Machine Learning Diffuse Optical Tomography Using Extreme Gradient Boosting and Genetic Programming. Bioengineering, 10(3), 382. MDPI AG. Retrieved from

Koresh Galil, Ami Hauptman, Rosit Levy Rosenboim, Prediction of corporate credit ratings with machine learning: Simple interpretative models, Finance Research Letters,
Volume 58, Part D, 2023, 104648

Hauptman, A., Benbassat, A. and Rosenboim, R. 2019. Evolving Predictions for Executive Pay Features in Board Networks. MENDEL. 25, 1 (Jun. 2019), 57-64.

A. Hauptman, Are Evolutionary-Computation Based Methods Comparable to other State-of-The-Art Methods for Community Detection? To appear in LateBreaking Abstracts of the Genetic and Evolutionary Computation Conference (GECCO 2016). Denver, Colorado July 17-24, 2016.

A. Elyasaf, A. Hauptman, and M. Sipper. Evolutionary Design of FreeCell Solvers. IEEE Transactions on Computational Intelligence and AI in Games, 4(4):270 –281, December 2012. Best Paper Award.

A. Elyasaf, A. Hauptman, and M. Sipper. GA-FreeCell: Evolving Solvers for the Game of FreeCell. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2011). Dublin, Ireland, July 12-16, 2011. ACM.

A. Elyasaf, Y. Zaritsky, A. Hauptman, and M. Sipper. Evolving Solvers for FreeCell and the Sliding-Tile Puzzle. In Proceedings of the Fourth Annual Symposium on Combinatorial Search, (SoCS 2011). Castell de Cardona, Barcelona, Spain, July 2011.

A. Hauptman, A. Elyasaf, and M. Sipper. Evolving hyper heuristic-based solvers for Rush Hour and FreeCell. In Proceedings of the 3rd Annual Symposium on Combinatorial Search (SoCS 2010), July 2010