Learning STRIPS operators from noisy and incomplete observations

Uncertainty in Artificial Intelligence - Proceedings of the 28th Conference, UAI 2012

Volumn , Issue , 2012, Pages 614-623

  Mourao, Kira ^a   Zettlemoyer, Luke ^b   Petrick, Ronald P A ^a   Steedman, Mark ^a  

^a UNIVERSITY OF EDINBURGH   (United Kingdom)

^b UNIVERSITY OF WASHINGTON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DOMAIN DESCRIPTION; DOMAIN DYNAMICS; EXTERNAL SENSORS; INCOMPLETE OBSERVATION; INTERNATIONAL PLANNING COMPETITIONS; PLANNING DOMAINS; REAL WORLD DOMAIN; TRANSITION FUNCTIONS;

ARTIFICIAL INTELLIGENCE;

AUTONOMOUS AGENTS;

EID: 84885976211     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (28)

1. Amir, E. and Chang, A. (2008). Learning partially observable deterministic action models. JAIR, 33, 349-402.
2. Benson, S. S. (1996). Learning Action Models for Reactive Autonomous Agents. Ph.D. thesis, Stanford University.
3. Croonenborghs, T., Ramon, J., Blockeel, H., and Bruynooghe, M. (2007). Online learning and exploiting relational models in reinforcement learning. In Proc. of IJCAI 2007, pages 726-731.
4. Do?gar, M. R., Ç akmak, M., U?gur, E., and Ş ahin, E. (2007). From primitive behaviors to goal directed behavior using affordances. In Proc. of IROS 2007, pages 729-734.
5. Fikes, R. E. and Nilsson, N. J. (1971). STRIPS: A new approach to the application of theorem proving to problem solving. Artif. Intell., 2, 189-208.
6. Freund, Y. and Schapire, R. (1999). Large margin classification using the perceptron algorithm. Machine Learning, 37, 277-96.
7. Gil, Y. (1994). Learning by experimentation: Incremental refinement of incomplete planning domains. In Proc. of ICML 1994, pages 87-95.
8. Guyon, I., Weston, J., Barnhill, S., and Vapnik, V. (2002). Gene selection for cancer classification using support vector machines. Machine Learning, 46(1-3), 389-422.
9. Halbritter, F. and Geibel, P. (2007). Learning models of relational MDPs using graph kernels. In Proc. of MICAI 2007, pages 409-419.
10. Haussler, D. (1989). Learning conjunctive concepts in structural domains. Machine Learning, 4(1), 7-40.
11. Khardon, R. and Servedio, R. A. (2005). Maximum margin algorithms with Boolean kernels. JMLR, 6, 1405-1429.
12. Khardon, R. and Wachman, G. M. (2007). Noise tolerant variants of the perceptron algorithm. JMLR, 8, 227-248.
13. Khardon, R., Roth, D., and Servedio, R. A. (2005). Efficiency versus convergence of Boolean kernels for online learning algorithms. JAIR, 24, 341-356.
14. Kohavi, R. and John, G. H. (1997). Wrappers for feature subset selection. Artif. Intell., 97(1-2), 273-324.
15. Metta, G. and Fitzpatrick, P. (2003). Early integration of vision and manipulation. Adaptive Behavior, 11(2), 109-128.
16. Mitchell, T. (1982). Generalization as search. Artif. Intell., 18(2), 203-226.
17. Modayil, J. and Kuipers, B. (2008). The initial development of object knowledge by a learning robot. Robotics and Autonomous Systems, 56(11), 879-890.
18. Mourao, K. (2012). Learning Action Representations Using Kernel Perceptrons. Ph.D. thesis, University of Edinburgh.
19. Mourao, K., Petrick, R. P. A., and Steedman, M. (2009). Learning action effects in partially observable domains (1). In Proc. of ICAPS 2009 Workshop on Planning and Learning, pages 15-22.
20. Mourao, K., Petrick, R. P. A., and Steedman, M. (2010). Learning action effects in partially observable domains (2). In Proc. of ECAI 2010, pages 973-974.
21. Pasula, H., Zettlemoyer, L. S., and Kaelbling, L. P. (2007). Learning symbolic models of stochastic domains. JAIR, 29, 309-352.
22. Rodrigues, C., Gerard, P., and Rouveirol, C. (2010). Incremental learning of relational action models in noisy environments. In Proc. of ILP 2010, pages 206-213.
23. Sadohara, K. (2001). Learning of Boolean functions using support vector machines. In Proc. of ALT, pages 106-118.
24. Valiant, L. G. (1985). Learning disjunctions of conjunctions. In Proc. of IJCAI 1985-Volume 1, pages 560-566.
25. Van Rijsbergen, C. J. (1979). Information Retrieval. Butterworth- Heinemann, 2nd edition.
26. Wang, X. (1995). Learning by observation and practice: An incremental approach for planning operator acquisition. In Proc. of ICML 1995, pages 549-557.
27. Yang, Q., Wu, K., and Jiang, Y. (2007). Learning action models from plan examples using weighted MAX-SAT. Artif. Intell., 171(2-3), 107-143.
28. Zhuo, H. H., Yang, Q., Hu, D. H., and Li, L. (2010). Learning complex action models with quantifiers and logical implications. Artif. Intell., 174(18), 1540-1569.