Research Areas

Knowledge representation in multiagent graphical models
Uncertain knowledge represenation
Probabilistic inference in multiagent graphical models
Probabilistic inference in Bayesian networks
Inference in dynamic Bayesian networks
Optimal collaborative design in supply chains
Knowledge discovery from data
Causal modeling in uncertain knowledge acquisition
Parallel computation
Simulation
Decision aid in medical diagnosis
Equipment monitoring and trouble-shooting
Intelligent home applications
Industrial scheduling
Risk assessment

Sample Publications by Research Area

Knowledge representation in multiagent graphical models
- Y. Xiang, Probabilistic Reasoning in Multiagent Systems: A Graphical Models Approach. Cambridge University Press, 2002.
  [A review of the book is published by Alex M. Andrew in Kybernetes: The International Journal of Systems & Cybernetics, Vol.32, No.7/8, 2003.]
- Y. Xiang and V. Lesser, On the Role of Multiply Sectioned Bayesian Networks to Cooperative Multiagent Systems. IEEE Trans. Systems, Man, and Cybernetics-Part A, Vol.33, No.4, 489-501, 2003.
- Y. Xiang, K.G. Olesen and F.V. Jensen, Practical Issues in Modeling Large Diagnostic Systems with Multiply Sectioned Bayesian Networks, International Journal of Pattern Recognition and Artificial Intelligence, Vol.14, No.1, 59-71, 2000.
- Y. Xiang, Verification of dag structures in cooperative belief network based multi-agent systems, Networks , 31: 183-191, 1998.
- Y. Xiang, A probabilistic framework for cooperative multi-agent distributed interpretation and optimization of communication, Artificial Intelligence, Vol.87, No.1-2, p295-342, 1996.
- Y. Xiang, D. Poole and M. P. Beddoes, Multiply Sectioned Bayesian Networks and Junction Forests for Large Knowledge Based Systems, Computational Intelligence, Vol.9, No.2, 171-220, 1993.
- Y. Xiang, Semantics of Multiply Sectioned Bayesian Networks for Cooperative Multi-agent Distributed Interpretation, G. McCalla, (Ed.), Advances in Artificial Intelligence , Springer, p213-226, 1996.
- Y. Xiang and V. Lesser, Justifying multiply sectioned Bayesian networks. Proc. 6th Inter. Conf. on Multi-agent Systems, 349-356, Boston, 2000.
- Y. Xiang, K.G. Olesen and F.V. Jensen, Some Practical Issues in Modeling Diagnostic Systems with Multiply Sectioned Bayesian Networks, 12th Florida Artificial Intelligence Research Symposium, 438-443, Orlendo, 1999.
- Y. Xiang, Multi-agent distributed interpretation with multiply sectioned Bayesian networks. Prepared for International Workshop on Multi-Agent Systems, MIT . Published at ftp.ai.mit.edu, pages 1-34, Oct. 1997.
- Y. Xiang, D. Poole and M. P. Beddoes, Exploring Localization In Bayesian Networks For Large Expert Systems, Proc. Eighth Conference on Uncertainty in Artificial Intelligence, Stanford, CA, 344-351, 1992.
Uncertain knowledge represenation
- Y. Xiang, M.P. Beddoes and D. Poole, Can uncertainty management be realized in a finite totally ordered probability algebra? In M. Henrion, R.D. Shachter, L.N. Kanal, and J.F. Lemmer, editors, Uncertainty in Artificial Intelligence 5, pages 41-57. North-Holland, 1990.
- S.K.M. Wong, C.J. Butz and Y. Xiang, A method for implementing a probabilistic model as a relational database, Proc. of 11th Conf. on Uncertainty in Artificial Intelligence, Montreal, p556-564, 1995.
- S.K.M. Wong, Y. Xiang and X. Nie, Representation of Bayesian Networks as Relational Databases, 5th International Conference on Information Processing & Management of Uncertainty in Knowledge-based Systems, 159-165, 1994.
Probabilistic inference in multiagent graphical models
- Y. Xiang, F.V. Jensen and X. Chen, Inference in Multiply Sectioned Bayesian Networks: Methods and Performance Comparison. Accepted and in the press by IEEE Trans. Systems, Man, and Cybernetics, 2006.
- Y. Xiang, Comparision of multiagent inference methods in multiply sectioned Bayesian networks. Inter. J. Approximate Reasoning, Vol.33, No.3, pages 235-254, August 2003.
- Y. Xiang, Cooperative triangulation in MSBNs without revealing subnet structures, Networks Vol.37, No.1, 53-65, 2001.
- Y. Xiang, Belief updating in multiply sectioned Bayesian networks without repeated local propagations, International Journal of Approximate Reasoning, 23: 1-21, 2000.
- Y. Xiang and X. Chen, Lazy inference in multiply sectioned Bayesian networks using linked junction forests. To appear in Advances in Bayesian Networks, 16 pages, 2006.
- Y. Xiang, Distributed multi-agent probabilistic reasoning with Bayesian networks, Z.W. Ras and M. Zemankova (Eds.), Methodologies for Intelligent Systems, Springer-Verlag, 285-294, 1994.
- Y. Xiang and K. Zhang, Agent Interface Enhancement: Making Multiagent Graphical Models Accessible. Accepted to appear in Proc. 5th Inter. Joint Conf. on Autonomous Agents and Multiagent Systems (AAMAS'06), 8 pages, 2006.
- Y. Xiang and X. Chen, Inference in multiply sectioned Bayesian networks with lazy propagation and linked jounction forests, Procs. 2nd European Workshop on Probabilistic Graphical Models, 217-224, 2004.
- X. An, Y. Xiang, and N. Cercone, Cooperative computation of Markov boundaries for efficient observation in multiagent probabilistic inference, Procs. 2nd European Workshop on Probabilistic Graphical Models, 9-16, 2004.
- X. An, Y. Xiang, and N. Cercone, Revising Markov Boundary for multiagent probabilistic inference, Procs. IEEE/WIC/ACM Inter. Conf. on Intelligent Agent Technology, 113-119, 2004.
- Y. Xiang, Comparing Alternative Methods for Inference in Multiply Sectioned Bayesian Networks. Proc. 15th Florida Artificial Intelligence Research Society Conf., 534-538, Pensacola, 2002.
- H. Geng and Y. Xiang. Distributed multi-agent MSBN: Implementing verification. In Proc. 13th Inter. Florida Artificial Intelligence Research Society Conf., pages 293--297, Orlendo, 2000.
- Y. Xiang and F.V. Jensen, Inference in Multiply Sectioned Bayesian Networks with Extended Shafer-Shenoy and Lazy Propagation, Proc. 15th Conf. on Uncertainty in Artificial Intelligence, 680-687, Stockholm, 1999.
- Y. Xiang and X. Chen, Interface Verification for Multagent Probabilistic Inference. In J.A. Gamez, S. Moral, and A. Salmeron (Eds.), Advances in Bayesian Networks, 19-38, 2004.
- Y. Xiang and X. Chen, Cooperative Verification of Agent Interface, Procs. 1st European Workshop on Probabilistic Graphical Models, 194-203, 2002.
- H. Geng and Y. Xiang, Implementation of fully distributed inference in multiagent MSBN systems, Proc. IEEE Canadian Conf. on Electrical and Computer Engineering, 1698-1703, Edmonton, 1999.
- Y. Xiang, Distributed Structure Verification in multiply sectioned Bayesian networks, Proc. Florida Artificial Intelligence Research Symposium , 295-299, 1996.
- Y. Xiang, Distributed scheduling of multiagent communication, Proc. 1st International Conf. on Multi-agent Systems, San Francisco, p390-397, 1995.
- Y. Xiang, Optimization of inter-subnet belief updating in multiply sectioned Bayesian networks, Proc. of 11th Conf. on Uncertainty in Artificial Intelligence, Montreal, p565-573, 1995.
Probabilistic inference in Bayesian networks
- Y. Xiang and V. Lesser, A Constructive Graphical Model Approach For Knowledge-Based Systems: A Vehicle Monitoring Case Study. Computational Intelligence, Vol.19, No.3, pages 284-309, 2003.
- Y. Xiang and C. Ye, A simple method to evaluate influence diagrams. Proc. 3rd Inter. Conf. on Cognitive Science, 2001.
- Y. Xiang and V. Lesser, A constructive Bayesian approach for vehicle monitoring. In Proc. 3rd Inter. Conf. on Information Fusion, ThC2 14--21, Paris, 2000.
- Y. Xiang, Computing the Lower-Bounded Composite Hypothesis by Belief Updating, Proc. Ninth Canadian Conference on Artificial Intelligence, Vancouver, BC, 98-105, 1992.
- Y. Xiang, M.P. Beddoes and D. Poole, Sequential Updating Conditional Probability in Bayesian Networks by Posterior Probability, Proc. 8th Biennial Conf. Canadian Society for Computational Studies of Intelligence, Ottawa, 21-27, 1990.
Inference in dynamic Bayesian networks
- Y. Xiang, Temporally invariant junction tree for inference in dynamic Bayesian network. Invited contribution in M. Wooldridge and M. Veloso, editors, Artificial Intelligence Today: Recent Trends and Developoments, page 473-487, Springer, 1999.
- X. An, Y. Xiang, and N. Cercone, Probabilistic Reasoning in Dynamic Multiagent Systems, Proc. 10th Inter. Workshop on Non-Monotonic Reasoning, pages 16-24, 2004.
Optimal collaborative design in supply chains
- Y. Xiang, J. Chen, and A. Deshmukh, A Decision-Theoretic Graphical Model For Collaborative Design On Supply Chains. In A.Y. Tawfik and S.D. Goodwin (Eds.), Advances in Artificial Intelligence, LNAI 3060, pages 355-369, 2004.
- Y. Xiang, J. Chen, and W.S. Havens, Optimal Design in Collaborative Design Network. Proc. 4th Inter. Joint Conf. on Autonomous Agents and Multiagent Systems (AAMAS'05), pages 241-248, 2005.
- J. Jones, Y. Xiang and S. Joseph, Bayesian Probabilistic Reasoning in Design, Proc. IEEE Ninth Pacific Rim Conference on Communications, Computers and Signal Processing, Victoria, BC, 501-504, 1993.
Knowledge discovery from data
- Y. Xiang and J. Lee, Learning Decomposable Markov Networks in Pseudo-Independent Domains with Local Evaluation. Machine Learning, 2006.
- J. Lee and Y. Xiang, Complexity Measurement of Fundamental Pseudo-independencet Models. Accepted to appear in International Journal of Approximate Reasoning, 2006.
- Y. Xiang, J. Lee and N. Cercone, Towards Better Scoring Metrics For Pseudo-Independent Models . International Journal of Intelligent Systems, Vol.19, No.8, pages 749-768, 2004.
- S.K.M. Wong, C.J. Butz, and Y. Xiang, Automated database schema design using mined data dependencies, J. Amer. Soci. Infor. Science, 49 (5):455-470, 1998.
- Y. Xiang, S.K.M. Wong and N. Cercone. A `Microscopic' study of minimum entropy search in learning decomposable Markov networks. Machine Learning, Vol.26, No.1, 65-92, 1997.
- Y. Xiang, S.K.M. Wong and N. Cercone. Quantification of uncertainty in classification rules discovered from databases. In Computational Intelligence , 11(2), pages 425-441, 1995.
- Y. Xiang, Pseudo Independent Models. In J. Wang (Ed.), Encyclopedia of Data Warehousing and Mining, pages 935-940, 2005.
- Y. Xiang and J. Lee, Local score computation in learning belief networks. In E. Stroulia and S. Matwin (editors), Advances in Artificial Intelligence, pages 152-161. Springer, 2001.
- Y. Xiang, J. Hu, N. Cercone and H. Hamilton, Learning Pseudo-Independent Models: Analytical and Experimental Results. H. Hamilton, (Ed.), Advances in in Artificial Intelligence, pages 227-239. Springer, 2000.
- Y. Xiang, S.K.M. Wong, and N. Cercone, Quantifying Uncertainty of Knowledge Discovered from Databases, W.P. Ziarko (Ed.), Rough Sets, Fuzzy Sets and Knowledge Discovery, Springer-Verlag, 63-73, 1994.
- J. Lee and Y. Xiang, Model complexity of pseudo-independent models. Proc. 18th Inter. Florida Artificial Intelligence Research Society Conf., pages 766-771, 2005.
- Y. Xiang, J. Lee, and N. Cercone, Parameterization of pseudo-independent models, Proc. 16th Florida Artificial Intelligence Research Society Conf., 521-525, 2003.
- Y. Huang and Y. Xiang, Learning Bayesian networks by learning decomposable Markov networks first, Proc. IEEE Canadian Conf. on Electrical and Computer Engineering, 1704-1709, Edmonton, 1999.
- Y. Xiang, A characterization of single-link search in learning belief networks, in Proc. Pacific Rim Knowledge Acquisition Workshop, 218-233, Singapore, 1998.
- Y. Xiang, Towards understanding of pseudo-independent domains, Poster Proc. 10th Inter. Symposium on Methodologies for Intelligent Systems, 221-232, Charlotte, 1997.
- J. Hu and Y. Xiang, Learning belief networks in domains with recursively embedded pseudo independent submodels, Proc. 13th Conf. on Uncertainty in Artificial Intelligence, 258--265, Providence, 1997.
- Y. Xiang, S.K.M Wong and N. Cercone. Critical Remarks on Single Link Search in Learning Belief Networks. In Proc. Uncertainty in Artificial Intelligence 96, 564-571, 1996.
- S.K.M. Wong and Y. Xiang, Construction of a Markov Network from Data for Probabilistic Inference, Proc. Third International Workshop on Rough Sets and Soft Computing, San Jose, CA, 562-569, 1994.
Causal modeling in uncertain knowledge acquisition
- Y. Xiang and N. Jia, Modeling causal reinforcement and undermining with noisy-AND trees. In L. Lamontagne and M. Marchand (Eds.), Canadian AI 2006, LNAI 4013, pages 171-182, 2006.
Parallel computation
- Y. Xiang and T. Chu, Parallel Learning of Belief Networks in Large and Difficult Domains, Data Mining and Knowledge Discovery, 3: 315-339, 1999.
- T. Chu and Y. Xiang, Exploring parallelism in learning belief networks, Proc. 13th Conf. on Uncertainty in Artificial Intelligence, 90--98, Providence, 1997.
- T. Chu and Y. Xiang, Parallel learning of belief networks, Proc. 10th Florida Artificial Intelligence Research Symposium, 192--197, Daytona Beach, 1997.
Simulation
- Y. Xiang, X. An and N. Cercone, Simulation of Graphical Models for Multiagent Probabilistic Inference . Simulation: Trans. Society for Modeling and Simulation, Vol.79, No.10, pages 545-567, 2003.
- Y. Xiang and T. Miller, A Well-Behaved Algorithm for Simulating Dependence Structures of Bayesian Networks, International Journal of Applied Mathematics, Vol.1, No.8, 923-932, 1999.
- X. An, Y. Xiang, and N. Cercone, A Dynamic Environment Simulator, Proc. European Simulation and Modelling Conference, 187-191, 2003.
- Y. Xiang and X. An, Generating Dependence Structure of Multiply Sectioned Bayesian Networks. Proc. 14th Florida Artificial Intelligence Research Society Conf., 613-618, Key West, 2001.
Decision aid in medical diagnosis
- Y. Xiang, B. Pant, A. Eisen, M.P. Beddoes, and D. Poole. Multiply sectioned Bayesian networks for neuromuscular diagnosis. Artificial Intelligence in Medicine , 5:293-314, 1993.
- Y. Xiang, A. Eisen, M. MacNeil, and M.P. Beddoes, Quality Control in Nerve Conduction Studies with Coupled Knowledge Based System Approach, Muscle and Nerve, Vol.15, No.2, 180-187, 1992.
- Y. Xiang, B. Pant, A. Eisen, M. P. Beddoes and D. Poole, PAINULIM: A Neuromuscular Diagnostic Aid Using Multiply Sectioned Bayesian Networks, Proc. ISMM International Conference on Mini and Microcomputers in Medicine and Healthcare, Long Beach, CA, 64-69, 1991.
Equipment monitoring and trouble-shooting
- Y. Xiang and H. Geng, Distributed Monitoring and Diagnosis with Multiply Sectioned Bayesian Networks, AAAI Spring symposium on AI in Equipment Service Maintenance and Support, 18-25, Sandford, 1999.
Intelligent home applications
- Y. Xiang and M. Janzen, A Computational Framework for Package Planning. Inter. J. Knowledge-Based and Intelligent Engineering Systems, Vol.10, No.2, 93-104, 2006.
- M. Janzen and Y. Xiang, Probabilistic reasoning for meal planning in intelligent fridges. In Y. Xiang and B. Chaib-draa (Eds.), Advances in Artificial Intelligence, LNAI 2671, pages 575-582, 2003.
- Y. Xiang, C. Ye, and D. Stacey, Application of Bayesian networks to shopping assistance. In R. Cohen and B. Spencer (Eds.), Advances in Artificial Intelligence, LNAI 2338, pages 344-348, 2002.
- Y. Xiang and M. Janzen, Package Planning with Graphical Models, Proc. 17th Inter. Florida Artificial Intelligence Research Society Conf., pages 874-879, 2004.
Industrial scheduling
- J.Y. Zhu, W.B.H Cooke, Y. Xiang and M. Chen, Optimal traffic flow schedules in a semi-parallel tree network, Computers and Industrial Engineering, Vol.29, No.1-4, 461-465, 1995.
- J.Y. Zhu, A. Deshmukh, Y. Xiang, and T. Middelkoop. Applying tree structure to aggregate scheduling in a flexible manufacture environment. Proc. 27th Inter. Conf. on Computers and Industrial Engineering, 2000.
Risk assessment
- J.Y. Zhu, W.B.H. Cooke and Y. Xiang, Application of Bayesian networks to quantified risk assessment, Proc. 5th Inter. Conf. Industrial Engineering and Management Science , 321-328, Beijing, 1998.