Programación Automática

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LECTURA OBLIGATORIA

1. Flener, P., & Schmid, U. (2008). An introduction to inductive programming. Artificial Intelligence Review, 29(1), 45-62.

2. Lowry, M., Philpot, A., Pressburger, T., & Underwood, I. (1994). Amphion: Automatic programming for scientific subroutine libraries. In Methodologies for Intelligent Systems (pp. 326-335). Springer Berlin Heidelberg.

3. Lowry, M., Philpot, A., Pressburger, T., & Underwood, I. (1994). Mo, D. H., & Witten, I. H. (1992). Learning text editing tasks from examples: a procedural approach. Behaviour & Information Technology, 11(1), 32-45.

4. Summers, P. D. (1977). A methodology for LISP program construction from examples. J. ACM. 24(1), 161{175. Reprinted in C. Rich and R. C. Waters, editors, Readings in Artificial Intelligence and Software Engineering, Morgan Kaufmann, 1986.

5. Smith, D. R. (1984). The synthesis of LISP programs from examples: A survey. In Biermann et al, A. W., editor, Automatic Program Construction Techniques, pages 307{324. Macmillan, New York, NY.

6. Sammut, C., Hurst, S., Kedzier, D., & Michie, D. (2002). 7 Learning to Fly. Imitation in animals and artifacts, 171.

7. Thurau, C., Bauckhage, C., & Sagerer, G. (2004, November). Imitation learning at all levels of game-AI. In Proceedings of the international conference on computer games, artificial intelligence, design and education (pp. 402-408).

8. Funes, P., Sklar, E., Juillé, H., & Pollack, J. (1998). Animal-animat coevolution: Using the animal population as fitness function. From Animals to Animats, 5, 525-533.

9. Olsson, R. (1995). Inductive functional programming using incremental program transformation. Artificial intelligence, 74(1), 55-81.

10. Salustowicz, R., & Schmidhuber, J. (1997). Probabilistic incremental program evolution. Evolutionary Computation, 5(2), 123-141.

11. Fernando Fernández, Manuela Veloso. Learning Domain Structure Through Probablistic Policy Reuse in Reinforcement Learning. Progress in Artificial Intelligence 2(1), 2013.

12. Fernando Fernández, Daniel Borrajo. Aprendizaje por Refuerzo. Capítulo 11 del libro Aprendizaje Automático: conceptos básicos y avanzados. Eds Basilio Sierra Araujo, Pearson Prentice Hall. 2006

13. Petrovic, P. (2005).Evolving automatons for distributed behavior arbitration. Pavel Petrovic. IDI/NTNU Technical Report 05/2005.

14. Sigaud, O., Wilson, S. W. (2007) Learning Classifier Systems: A Survey, Soft Computing 11(11), 1065-1078.

15. Urbanowicz, R. J., Moore, J.M (2009). Learning Classifier Systems: A Complete Introduction, Review, and Roadmap. Journal of Artificial Evolution and Applications. http://dx.doi.org/10.1155/2009/736398.

16. Riccardo Poli, William B. Langdon, Nicholas F. McPhee. A field guide to Genetic Programming. 2009. (URL). Completo libro sobre la Programación Genética (disponible en Internet).