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Volumn 1, Issue , 2012, Pages 368-376

Action-model based multi-agent plan recognition

Author keywords

[No Author keywords available]

Indexed keywords

ACTION MODELS; ACTIVITY SEQUENCE; DYNAMIC TEAMS; EMPIRICAL STUDIES; MULTIAGENT PLANS; MULTIAGENT TEAMS; PLAN LIBRARIES; SATISFIABILITY PROBLEMS;

EID: 84877754763     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (30)

References (20)
  • 1
    • 84881049716 scopus 로고    scopus 로고
    • Plan recognition in virtual laboratories
    • Ofra Amir and Yaakov (Kobi) Gal. Plan recognition in virtual laboratories. In Proceedings of IJCAI, 2011.
    • (2011) Proceedings of IJCAI
    • Amir, O.1    Gal, Y.2
  • 3
    • 80055036424 scopus 로고    scopus 로고
    • Branch and price for multi-agent plan recognition
    • Bikramjit Banerjee and Landon Kraemer. Branch and price for multi-agent plan recognition. In Proceedings of AAAI, 2011.
    • (2011) Proceedings of AAAI
    • Banerjee, B.1    Kraemer, L.2
  • 4
    • 77958543973 scopus 로고    scopus 로고
    • Multi-agent plan recognition: Formalization and algorithms
    • Bikramjit Banerjee, Landon Kraemer, and Jeremy Lyle. Multi-agent plan recognition: formalization and algorithms. In Proceedings of AAAI, 2010.
    • (2010) Proceedings of AAAI
    • Banerjee, B.1    Kraemer, L.2    Lyle, J.3
  • 5
    • 84880781178 scopus 로고    scopus 로고
    • A general model for online probabilistic plan recognition
    • Hung H. Bui. A general model for online probabilistic plan recognition. In Proceedings of IJCAI, 2003.
    • (2003) Proceedings of IJCAI
    • Bui, H.H.1
  • 6
    • 2842560201 scopus 로고
    • STRIPS: A new approach to the application of theorem proving to problem solving
    • R. Fikes and N. J. Nilsson. STRIPS: A new approach to the application of theorem proving to problem solving. Artificial Intelligence Journal, pages 189-208, 1971.
    • (1971) Artificial Intelligence Journal , pp. 189-208
    • Fikes, R.1    Nilsson, N.J.2
  • 7
    • 67349165700 scopus 로고    scopus 로고
    • A probabilistic plan recognition algorithm based on plan tree grammars
    • Christopher W. Geib and Robert P. Goldman. A probabilistic plan recognition algorithm based on plan tree grammars. Artificial Intelligence, 173(11):1101-1132, 2009.
    • (2009) Artificial Intelligence , vol.173 , Issue.11 , pp. 1101-1132
    • Geib, C.W.1    Goldman, R.P.2
  • 8
    • 85167429905 scopus 로고    scopus 로고
    • Model-lite planning for the web age masses: The challenges of planning with incomplete and evolving domain models
    • Subbarao Kambhampati. Model-lite planning for the web age masses: The challenges of planning with incomplete and evolving domain models. In AAAI, 2007.
    • (2007) AAAI
    • Kambhampati, S.1
  • 13
    • 77958537867 scopus 로고    scopus 로고
    • Probabilistic plan recognition using off-The-shelf classical planners
    • Miquel Ramrez and Hector Geffner. Probabilistic plan recognition using off-the-shelf classical planners. In Proceedings of AAAI, 2010.
    • (2010) Proceedings of AAAI
    • Ramrez, M.1    Geffner, H.2
  • 14
    • 77958566201 scopus 로고    scopus 로고
    • Recognizing multi-agent activities from gps data
    • Adam Sadilek and Henry Kautz. Recognizing multi-agent activities from gps data. In Proceedings of AAAI, 2010.
    • (2010) Proceedings of AAAI
    • Sadilek, A.1    Kautz, H.2
  • 15
    • 80055052226 scopus 로고    scopus 로고
    • Abductive Markov logic for plan recognition
    • Parag Singla and Raymond Mooney. Abductive markov logic for plan recognition. In Proceedings of AAAI, 2011.
    • (2011) Proceedings of AAAI
    • Singla, P.1    Mooney, R.2
  • 16
    • 57749185874 scopus 로고    scopus 로고
    • Hypothesis pruning and ranking for large plan recognition problems
    • Gita Sukthankar and Katia Sycara. Hypothesis pruning and ranking for large plan recognition problems. In Proceedings of AAAI, 2008.
    • (2008) Proceedings of AAAI
    • Sukthankar, G.1    Sycara, K.2
  • 18
    • 33847340622 scopus 로고    scopus 로고
    • Learning action models from plan examples using weighted MAX-SAT
    • February
    • Qiang Yang, Kangheng Wu, and Yunfei Jiang. Learning action models from plan examples using weighted MAX-SAT. Artificial Intelligence, 171:107-143, February 2007.
    • (2007) Artificial Intelligence , vol.171 , pp. 107-143
    • Yang, Q.1    Wu, K.2    Jiang, Y.3
  • 19
    • 84879489079 scopus 로고    scopus 로고
    • Multi-agent plan recognition with partial team traces and plan libraries
    • Hankz Hankui Zhuo and Lei Li. Multi-agent plan recognition with partial team traces and plan libraries. In Proceedings of IJCAI, 2011.
    • (2011) Proceedings of IJCAI
    • Zhuo, H.H.1    Li, L.2
  • 20
    • 78049307952 scopus 로고    scopus 로고
    • Learning complex action models with quantifiers and implications
    • Hankz Hankui Zhuo, Qiang Yang, Derek Hao Hu, and Lei Li. Learning complex action models with quantifiers and implications. Artificial Intelligence, 174(18):1540 - 1569, 2010.
    • (2010) Artificial Intelligence , vol.174 , Issue.18 , pp. 1540-1569
    • Zhuo, H.H.1    Yang, Q.2    Hu, D.H.3    Li, L.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.