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Robotics plus language learning
- S. R. K. Branavan, H. Chen, L. Zettlemoyer, and R. Barzilay, “Reinforcement learning for mapping instructions to actions,” in Proc. of the Joint Conf. of the 47th Annual Meeting of the ACL and the 4th Int’l Joint Conference on Natural Language Processing. Suntec, Singapore: Association for Computational Linguistics, August 2009, pp. 82–90
- J. Dzifcak, M. Scheutz, C. Baral, and P. Schermerhorn, “What to do and how to do it: Translating natural language directives into temporal and dynamic logic representation for goal management and action execution,” in Proc. of the 2009 IEEE Int’l Conf. on Robotics and Automation (ICRA ’09), Kobe, Japan, May 2009.
- K.-y. Hsiao, S. Tellex, S. Vosoughi, R. Kubat, and D. Roy, “Object schemas for grounding language in a responsive robot,” Connection Science, vol. 20, no. 4, pp. 253–276, 2008.
- Kai-yuh Hsiao, Stefanie Tellex, Soroush Vosoughi, Rony Kubat, and Deb Roy. Object schemas for grounding language in a responsive robot. Connect. Sci, 20(4):253–276, 2008.
- Thomas Kollar, Stefanie Tellex, Deb Roy, and Nicholas Roy. Toward understanding natural language directions. In Proceedings of HRI, 2010.
- V. Kruger, D. Kragic, A. Ude, and C. Geib. The meaning of action: A review on action recognition and mapping. Advanced Robotics, 21(13), 2007.
- M. Macmahon, B. Stankiewicz, and B. Kuipers, “Walk the talk: Connecting language, knowledge, action in route instructions,” in In Proc. of the Nat. Conf. on Artificial Intelligence (AAAI), 2006, pp. 1475–1482.
- Matt MacMahon, Brian Stankiewicz, and Benjamin Kuipers. Walk the talk: Connecting language, knowledge, and action in route instructions. Proceedings of the National Conference on Artificial Intelligence, pages 1475—1482, 2006.
- C. Matuszek, D. Fox, and K. Koscher. Following directions using statistical machine translation. In Proceedings of HRI, 2010.
- R. J. Mooney, “Learning to connect language and perception,” in Proc. of the Twenty-Third AAAI Conf. on Artificial Intelligence, AAAI 2008, D. Fox and C. P. Gomes, Eds. Chicago, Illinois: AAAI Press, July 2008, pp. 1598–1601.
- D. Roy, “Learning visually-grounded words and syntax for a scene description task,” Computer Speech and Language, 2002.
- D. Roy, “Semiotic schemas: a framework for grounding language in action and perception,” Artificial Intelligence, vol. 167, no. 1-2, pp. 170–205, 2005.
- P.E. Rybski, K. Yoon, J. Stolarz, and M.M. Veloso. Interactive robot task training through dialog and demonstration. In Proceedings of HRI, page 56. ACM, 2007.
- N. Shimizu and A. Haas, “Learning to Follow Navigational Route Instructions,” in Int’l Joint Conf. on Artificial Intelligence (IJCAI), 2009.
- Nobuyuki Shimizu and Andrew Haas. Learning to follow navigational route instructions. In IJCAI’09: Proceedings of the 21st international jont conference on Artifical intelligence, pages 1488–1493, San Francisco, CA, USA, 2009. Morgan Kaufmann Publishers Inc.
- M. Skubic, D. Perzanowski, S. Blisard, A. Schultz, W. Adams, M. Bugajska, and D. Brock, “Spatial language for human-robot dialogs,” IEEE Transactions on Systems, Man, and Cybernetics, Part C, Special Issue on Human-Robot Interaction, vol. 34, no. 2, pp. 154–167, May 2001.
- M. Skubic, D. Perzanowski, S. Blisard, A. Schultz, W. Adams, M. Bugajska, and D. Brock. Spatial language for human-robot dialogs. Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, 34(2):154–167, 2004. ISSN 1094-6977. doi: 10.1109/TSMCC.2004.826273.
- Adam Vogel and Dan Jurafsky. Learning to follow navigational directions. In ACL ’10: Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, pages 806–814, Morristown, NJ, USA, 2010. Association for Computational Linguistics.
- Y. Wei, E. Brunskill, T. Kollar, and N. Roy, “Where to go: Interpreting natural directions using global inference,” in Int’l Conf. on Robotics and Automation (ICRA), 2009.
- Yuan Wei, Emma Brunskill, Thomas Kollar, and Nick Roy. Where to go: Interpreting natural directions using global inference. In ICRA, 2009.
- B. Ziebart, A. Maas, A. Dey, and J. D. Bagnell, “Navigate like a cabbie: Probabilistic reasoning from observed context-aware behavior,” in UBICOMP: Ubiquitious Computation, 2008
P. Abbeel and A. Ng. Apprenticeship learning via inverse reinforcement learning. In Proc. ICML, 2004.
S. Ekvall and D. Kragic. Robot learning from demonstration: a task-level planning approach. International Journal of Advanced Robotic Systems, 5(3), 2008.
Lockwood, K., Forbus, K., Halstead, D., & User, J. Automatic Categorization of Spatial Prepositions. Proceedings of the 28th Annual Conference of the Cognitive Science Society. (2006).
M. Nicolescu and M. Mataric. Natural methods for robot task learning: instructive demonstrations, generalization and practice. In Proc. AAMAS, 2003.
J. Peters and J. Kober. Using reward-weighted imitation for robot reinforcement learning. In Proc. Inter. Symp. on Approximate Dynamic Programming and Reinforcement Learning, 2009.
Stefan Schaal, Auke Ijspeert, and Aude Billard. Computational approaches to motor learning by imitation. Philosophical Transactions of the Royal Society B: Biological Sciences, 358(1431): 537–547, March 2003. ISSN 0962-8436. PMID: 12689379 PMCID: 1693137.
David Silver, J. Andrew Bagnell, and Anthony Stentz. Perceptual interpretation for autonomous navigation through dynamic imitation learning. In Proc. ISRR, 2009. Thomas Kollar and Nick Roy. Utilizing object-object and object-scene context when planning to find things. In IEEE International Conference on Robotics and Automation, 2009.
to hunt down bibs for
Marianella Casasola - Leslie B. Cohen - "Infant categorization of containment, support and tight-fit spatial relationships" - In press: Developmental Science
Thomas Kollar, Stefanie Tellex, Deb Roy, and Nicholas Roy - "Grounding Verbs of Motion in Natural Language Commands to Robots" -
Kate Lockwood, Andrew Lovett, and Ken Forbus - Automatic Classification of Containment and Support Spatial Relations in English and Dutch