Fast hierarchical goal schema recognition

Proceedings of the National Conference on Artificial Intelligence

Volumn 1, Issue , 2006, Pages 796-801

  Blaylock, Nate ^a   Allen, James ^b  

^a CYCORP INC   (United States)

^b University of Rochester   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER GRAPHICS; HIERARCHICAL SYSTEMS; MARKOV PROCESSES; MATHEMATICAL MODELS; STATISTICAL METHODS;

CASCADING HIDDEN MARKOV MODELS; GRAPHICAL MODELS; HIERARCHICAL PLANS; MACHINE LEARNING TECHNIQUES;

LEARNING SYSTEMS;

EID: 33750681650     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (9)

1. Blaylock, N., and Allen, J. 2005a. Generating artificial corpora for plan recognition. In User Modeling 2005.
2. Blaylock, N., and Allen, J. 2005b. Recognizing instantiated goals using statistical methods. In Kaminka, G., ed., Workshop on Modeling Others from Observations.
3. Blaylock, N. J. 2005. Towards tractable agent-based dialogue. Technical Report 880, University of Rochester, Department of Computer Science. PhD thesis.
4. Bui, H. H.; Venkatesh, S.; and West, G. 2002. Policy recognition in the Abstract Hidden Markov Model. Journal of Artificial Intelligence Research 17.
5. Charniak, E. 1997. Statistical techniques for natural language parsing. AI Magazine 18(4).
6. Kautz, H. A. 1987. A formal theory of plan recognition. Technical Report 215, University of Rochester, Department of Computer Science. PhD thesis.
7. Murphy, K. P., and Paskin, M. A. 2001. Linear time inference in hierarchical HMMs. In NIPS-01.
8. Nau, D.; Au, T.-C.; Ilghami, O.; Kuter, U.; Murdock, J. W.; Wu, D.; and Yaman, F. 2003. SHOP2: An HTN planning system. Journal of Artificial Intelligence Research 20:379-404.
9. Pynadath, D. V., and Wellman, M. P. 2000. Probabilistic state-dependent grammars for plan recognition. In UAI-2000.