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Plan Recognition in Natural Language DialogueDecember 1990
Publisher:
  • MIT Press
  • 55 Hayward St.
  • Cambridge
  • MA
  • United States
ISBN:978-0-262-03167-7
Published:01 December 1990
Pages:
240
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Abstract

From the Publisher:

In most current natural language systems each query is treated as an isolated request for information regardless of its context in dialogue. Sandra Carberry addresses the problem of creating computational strategies that can improve user-computer communication by assimilating ongoing dialogue and reasoning on the acquired knowledge.

Plan Recognition in Natural Language Dialogue critically examines plan recognition - the inference of an agent's goals and how he or she intends to achieve them. It describes significant models of plan inference and presents in detail the author's own model, which infers new goals from user utterances and integrates them into the system's model of the user's plan, incrementally expanding and adding detail to its beliefs about what the information seeker wants to do. Carberry then outlines computational strategies for interpreting two kinds of problematic utterances: utterances that violate the pragmatic rules of the system's world model and intersentential elliptical fragments. She also suggests directions for future research.

Sandra Carberry is Assistant Professor in the Department of Computer and Information Sciences at the University of Delaware. Plan Recognition in Natural Language Dialogue is included in the ACL-MIT Press Series in Natural Language Processing edited by Aravind Joshi.

Cited By

  1. Kim J, Woicik M, Gombolay M, Son S and Shah J Learning to infer final plans in human team planning Proceedings of the 27th International Joint Conference on Artificial Intelligence, (4771-4779)
  2. Jiang Y, Warnell G, Munera E and Stone P A Study of Human-Robot Copilot Systems for En-route Destination Changing 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), (997-1004)
  3. Sukthankar G, Geib C, Bui H, Pynadath D and Goldman R (2014). Plan, Activity, and Intent Recognition, 10.5555/2671144, Online publication date: 10-Mar-2014.
  4. ACM
    Amir O and Gal Y (2013). Plan Recognition and Visualization in Exploratory Learning Environments, ACM Transactions on Interactive Intelligent Systems (TiiS), 3:3, (1-23), Online publication date: 1-Oct-2013.
  5. Bunt H Interpretation and generation of dialogue with multidimensional context models Proceedings of the Third COST 2102 international training school conference on Toward autonomous, adaptive, and context-aware multimodal interfaces: theoretical and practical issues, (214-242)
  6. Geib C Delaying commitment in plan recognition using combinatory categorial grammars Proceedings of the 21st International Joint Conference on Artificial Intelligence, (1702-1707)
  7. Geib C and Steedman M On natural language processing and plan recognition Proceedings of the 20th international joint conference on Artifical intelligence, (1612-1617)
  8. Michalak P and Allen J Improving User Taught Task Models Proceedings of the 11th international conference on User Modeling, (375-379)
  9. Armentano M and Amandi A (2007). Plan recognition for interface agents, Artificial Intelligence Review, 28:2, (131-162), Online publication date: 1-Aug-2007.
  10. Kanno T, Nakata K and Furuta K (2006). A method for conflict detection based on team intention inference, Interacting with Computers, 18:4, (747-769), Online publication date: 1-Jul-2006.
  11. ACM
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  12. Mott B, Lee S and Lester J Probabilistic goal recognition in interactive narrative environments Proceedings of the 21st national conference on Artificial intelligence - Volume 1, (187-192)
  13. Thompson C, Göker M and Langley P (2004). A personalized system for conversational recommendations, Journal of Artificial Intelligence Research, 21:1, (393-428), Online publication date: 1-Jan-2004.
  14. Blaylock N and Allen J Statistical goal parameter recognition Proceedings of the Fourteenth International Conference on International Conference on Automated Planning and Scheduling, (297-304)
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  16. Blaylock N and Allen J Corpus-based, statistical goal recognition Proceedings of the 18th international joint conference on Artificial intelligence, (1303-1308)
  17. Elzer S, Green N, Carberry S and McCoy K Extending plan inference techniques to recognize intentions in information graphics Proceedings of the 9th international conference on User modeling, (122-132)
  18. Fernández R and Ginzburg J Non-sentential utterances Proceedings of the 19th international conference on Computational linguistics - Volume 1, (1-7)
  19. Fernández R and Ginzburg J Non-sentential utterances in dialogue Proceedings of the 3rd SIGdial workshop on Discourse and dialogue - Volume 2, (15-26)
  20. Xu W, Xu B, Huang T and Xia H Bridging the gap between dialogue management and dialogue models Proceedings of the 3rd SIGdial workshop on Discourse and dialogue - Volume 2, (201-210)
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  22. Carberry S (2019). Techniques for Plan Recognition, User Modeling and User-Adapted Interaction, 11:1-2, (31-48), Online publication date: 27-Mar-2001.
  23. Oviatt S, Cohen P, Wu L, Vergo J, Duncan L, Suhm B, Bers J, Holzman T, Winograd T, Landay J, Larson J and Ferro D (2018). Designing the user interface for multimodal speech and pen-based gesture applications, Human-Computer Interaction, 15:4, (263-322), Online publication date: 1-Dec-2000.
  24. Bagga A, Strzalkowski T and Wise G PartsID Proceedings of the sixth conference on Applied natural language processing, (29-36)
  25. Bagga A, Stein G and Strzalkowski T FidelityXPress Content-Based Multimedia Information Access - Volume 1, (803-811)
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  27. Hagen E (1999). An Approach to Mixed Initiative Spoken Information Retrieval Dialogue, User Modeling and User-Adapted Interaction, 9:1-2, (167-213), Online publication date: 1-Jan-1999.
  28. Green N and Carberry S (1999). A Computational Mechanism for Initiative in Answer Generation, User Modeling and User-Adapted Interaction, 9:1-2, (93-132), Online publication date: 1-Jan-1999.
  29. Reuer V Dialogue processing in a CALL-system Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics, (253-256)
  30. Carberry S and Lambert L (1999). A process model for recognizing communicative acts and modeling negotiation subdialogues, Computational Linguistics, 25:1, (1-53), Online publication date: 1-Mar-1999.
  31. Green N and Carberry S (1999). Interpreting and generating indirect answers, Computational Linguistics, 25:3, (389-435), Online publication date: 1-Sep-1999.
  32. ACM
    Wærn A Local plan recognition in direct manipulation interfaces Proceedings of the 2nd international conference on Intelligent user interfaces, (7-14)
  33. Agarwal R Towards a PURE spoken dialogue system for information access Interactive Spoken Dialog Systems on Bringing Speech and NLP Together in Real Applications, (90-97)
  34. Biermann A, Fulkerson M and Keim G Speech-graphics dialogue systems Interactive Spoken Dialog Systems on Bringing Speech and NLP Together in Real Applications, (121-126)
  35. Jönsson A (1997). A model for habitable and efficient dialogue management for natural language interaction, Natural Language Engineering, 3:2, (103-122), Online publication date: 1-Sep-1997.
  36. Passonneau R and Litman D (1997). Discourse segmentation by human and automated means, Computational Linguistics, 23:1, (103-139), Online publication date: 1-Mar-1997.
  37. ACM
    Eller-Meshreki R, Saundurs T and Meshreki S An architecture for planning with external information points in a real-time system Proceedings of the 1996 ACM 24th annual conference on Computer science, (58-66)
  38. Allen J, Miller B, Ringger E and Sikorski T A robust system for natural spoken dialogue Proceedings of the 34th annual meeting on Association for Computational Linguistics, (62-70)
  39. Hirschberg J and Nakatani C A prosodic analysis of discourse segments in direction-giving monologues Proceedings of the 34th annual meeting on Association for Computational Linguistics, (286-293)
  40. Lokuge I and Ishizaki S GeoSpace Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, (409-414)
  41. Smith R, Biermann A and Hipp D (1995). An architecture for voice dialog systems based on prolog-style theorem proving, Computational Linguistics, 21:3, (281-320), Online publication date: 1-Sep-1995.
  42. McRoy S and Hirst G (1995). The repair of speech act misunderstandings by abductive inference, Computational Linguistics, 21:4, (435-478), Online publication date: 1-Dec-1995.
  43. Traum D and Allen J Discourse obligations in dialogue processing Proceedings of the 32nd annual meeting on Association for Computational Linguistics, (1-8)
  44. Green N and Carberry S A hybrid reasoning model for indirect answers Proceedings of the 32nd annual meeting on Association for Computational Linguistics, (58-65)
  45. Nagao K and Takeuchi A Social interaction Proceedings of the Twelfth AAAI National Conference on Artificial Intelligence, (22-28)
  46. Ferguson G and Allen J Generic plan recognition for dialogue systems Proceedings of the workshop on Human Language Technology, (171-176)
  47. Biermann A, Guinn C, Hipp D and Smith R Efficient collaborative discourse Proceedings of the workshop on Human Language Technology, (177-181)
  48. Passonneau R and Litman D Intention-based segmentation Proceedings of the 31st annual meeting on Association for Computational Linguistics, (148-155)
  49. Ardissono L, Lombardo A and Sestero D A flexible approach to cooperative response generation in information-seeking dialogues Proceedings of the 31st annual meeting on Association for Computational Linguistics, (274-276)
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  52. Green N and Carberry S Conversational implicatures in indirect replies Proceedings of the 30th annual meeting on Association for Computational Linguistics, (64-71)
  53. Kitano H and Van Ess-Dykema C Toward a plan-based understanding model for mixed-initiative dialogues Proceedings of the 29th annual meeting on Association for Computational Linguistics, (25-32)
  54. Ramshaw L A three-level model for plan exploration Proceedings of the 29th annual meeting on Association for Computational Linguistics, (39-46)
Contributors
  • University of Delaware

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