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Volumn WS-07-09, Issue , 2007, Pages 74-81

Multi-agent behaviour segmentation via spectral clustering

Author keywords

[No Author keywords available]

Indexed keywords

INTENT RECOGNITION; MULTI AGENTS; MULTI-AGENT INTERACTIONS; SIMILARITY MEASURING; SPACE AND TIME; SPECTRAL CLUSTERING; TECHNICAL REPORTS; TEMPORAL DOMAINS; TEMPORAL PROPERTIES;

EID: 51849093416     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (7)

References (21)
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  • 3
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    • Needles in a haystack: Plan recognition in large spatial domains involving multiple agents
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    • Devaney, M.1    Ram, A.2
  • 5
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    • Learning a manifold-constrained map between image sets: Applications to matching and pose estimation
    • Ham, J.; Ahn, I.; and Lee, D. 2006. Learning a manifold-constrained map between image sets: applications to matching and pose estimation. In CVPR06.
    • (2006) CVPR , vol.6
    • Ham, J.1    Ahn, I.2    Lee, D.3
  • 6
    • 14344257134 scopus 로고    scopus 로고
    • A spatio-temporal extension to isomap nonlinear dimension reduction
    • Jenkins, O. C., and Mataric, M. J. 2004. A spatio-temporal extension to isomap nonlinear dimension reduction. In Proceedings ICML, 441-448.
    • (2004) Proceedings ICML , pp. 441-448
    • Jenkins, O.C.1    Mataric, M.J.2
  • 8
    • 34547988736 scopus 로고    scopus 로고
    • Proto-value functions: A Laplacian framework for learning representation and control in Markov decision processes
    • Technical Report 2006-35
    • Mahadevan, S., and Maggioni, M. 2006. Proto-value functions: A Laplacian framework for learning representation and control in Markov decision processes. Technical Report 2006-35.
    • (2006)
    • Mahadevan, S.1    Maggioni, M.2
  • 11
    • 33745821896 scopus 로고    scopus 로고
    • Spectral clustering for robust motion segmentation
    • Pajdla, T, and Matas, J, eds, ECCV 2004, number in, Springer-Verlag Berlin, Heidelberg
    • Park, J.; Zha, H.; and Kasturi, R. 2004. Spectral clustering for robust motion segmentation. In Pajdla, T., and Matas, J., eds., ECCV 2004, number 3024 in LNCS, 390-401. Springer-Verlag Berlin, Heidelberg.
    • (2004) LNCS , vol.3024 , pp. 390-401
    • Park, J.1    Zha, H.2    Kasturi, R.3
  • 15
    • 31844447221 scopus 로고    scopus 로고
    • Identifying useful subgoals in reinforcement learning by local graph partitioning
    • Proceedings of the Twenty-Second International Conference on Machine Learning, of
    • Şimşek, Ö.; Wolfe, A. P.; and Barto, A. G. 2005. Identifying useful subgoals in reinforcement learning by local graph partitioning. In Proceedings of the Twenty-Second International Conference on Machine Learning, volume 119 of ACM International Conference Proceeding Series, 816-823.
    • (2005) ACM International Conference Proceeding Series , vol.119 , pp. 816-823
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  • 16
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    • Robust recognition of physical team behaviors using spatio-temporal models
    • Sukthankar, G., and Sycara, K. 2006. Robust recognition of physical team behaviors using spatio-temporal models. In Proceedings of AAMAS, 638-645.
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    • Graph partition model for robust temporal data segmentation
    • Ho, T, Cheung, D, and Liu, H, eds, PAKDD 2005, number in, Springer-Verlag Berlin, Heidelberg
    • Yuan, J.; Zhang, B.; and Lin, F. 2005. Graph partition model for robust temporal data segmentation. In Ho, T.; Cheung, D.; and Liu, H., eds., PAKDD 2005, number 3518 in LNAI, 758-763. Springer-Verlag Berlin, Heidelberg.
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    • Yuan, J.1    Zhang, B.2    Lin, F.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.