Books

Shen, W-M.,  Autonomous Learning from the Environment (355 pages), W. H. Freeman, Computer Science Press, 1994. (Foreword by Herbert A. Simon)
Shen, W.M., Edited, Learning Actions Models, AAAI Press, 1999.

Journal Publications

  1. Shen WM, Adibi J, Adobbati R, et al.  Integrated reactive soccer agents,   LECT NOTES ARTIF INT 1604: 286-298, 1999.
  2. Shen, WM.,  J. Adibi,  R. Adobbati, B. Cho, A. Erdem, H. Moradi, B. Salemi, and S. Tejada.  Towards Integrated Soccer Robots, AI Magazine, 19(3) 79-85, 1998.
  3. Tambe, M. and L. Johnson and W-M. Shen.  Adaptive Agent Tracking in Real-world Multi-Agent Domains: A Preliminary Report.  International Journal of Human-Computer Studies, 48, 105-124, 1998.
  4. Shen, WM.,  J. Adibi,  B. Cho, G. Kaminka,  J. Kim,  B. Salemi, and S. Tejada. YODA: The Young Observant Discovery Agent, AI Magazine. 18(1) 37-45, 1997.
  5. Patil, R. and W. Zhang and WM. Shen. An Information Mediator Network for Tasks in Dynamic Environments. IMIA Yearbook of Medical Informatics, 1996.
  6. Y. Arens, C. Knoblock, and WM. Shen.  Query Reformulation for Dynamic Information Integration.  Journal of Intelligent Information Systems, 6, 99-130, 1996.
  7. Shen, WM.  The Process of Discovery. Foundations of Science, 1(2), 1995.
  8. Shen, WM.  Discovery as autonomous learning from the environment.  Machine Learning , 12, 143-156, 1993.
  9. Shen, WM. and H.A. Simon.  Fitness requirements for scientific theories containing recursive theoretical terms. British Journal of Philosopy of Science, 44, 641-652, 1993.
  10. Shen, WM. Discovering regularities from knowledge bases. International Journal of Intelligent Systems, 7(7), 623--636, 1992.
  11. Shen, WM. LIVE: An architecture for autonomous learning from the environment, ACM SIGART Bulletin, Special issue on Integrated Cognitive Architectures, 2(4), 151-155, 1992.
  12. Shen, WM. and C. Collet and M.N. Huhns. Resource integration using a large knowledge base in Carnot. IEEE Computer, 24(12), 55-62, 1991.
  13. Shen, WM.  Functional Transformation in AI Discovery Systems. Artificial Intelligence , 41(3), 257-272, 1989.

Book Chapters

  1. Woelk, D., M. Huhns, N. Jacobs, T. Ksiezyk, K. Ong, WM. Shen, M. Singh, and C. Tomlinson. 1995. Carnot Prototype. In Heterogeneous Databases, edited by Omran A. Bukhres and Ahmed Elmagarmid. MIT Press.
  2. Shen, WM. 1994. Learning deterministic finite automata using local distinguishing experiments. In Computational Learning Theory and Natural Learning Systems, edited by T. Petsche and S. Judd and S. Hanson. MIT Press.

Refereed Conference Papers

  1. P J Modi, H Jung, M Tambe, W-M Shen & S Kulkarni, A Dynamic Distributed Constraint Satisfaction Approach to Resource Allocation, the 7th International Conference on Principles and Practice of Constraint Programming, Paphos, Cyprus, 2001.
  2. Pragnesh Jay Modi, Wei-Min Shen, Collaborative Multiagent Learning for Classification Tasks, Proceedings of the 5th International Conference on Autonomous Agents Workshop on Learning Agents, Montreal, Quebec, 2001.
  3. Pragnesh Jay Modi, Hyuckchul Jung, Milind Tambe, Wei-Min Shen, Shriniwas Kulkarni, Dynamic Distributed Resource Allocation: A Distributed Constraint Satisfaction Approach, in the Proceedings of Agent Theories, Architectures and Languages, Seattle, WA, 2001.
  4. Pragnesh Jay Modi, Wei-Min Shen, Learning Team Coordination Constraints through Execution,  Proceedings of International Conference on MultiAgent Systems (poster), Boston, MA, 2000.
  5. Pragnesh Jay Modi, Wei-Min Shen, Learning Team Coordination Constraints through Execution, in Proceedings of International Conference on MultiAgent Systems (poster), Boston, MA, 2000.
  6. Tambe, M., WM. Shen, M. Mataric, D. Goldberg, J. Modi, Z. Qiu, and B. Salemi. Teamwork in Cyberspace: Using TEAMCORE to make agents team-ready. Proceedings of AAAI Spring Symposium on Agents in Cyberspace, pp 136-141, Stanford, California, 1999.
  7. Shen, WM., W. Zhang, X. Wang, and Y. Arens. Model construction with key identification, Proceedings of SPIE Symposium on Data Mining and Knowledge Discovery: Theory, Tools, and Technology, SPIE Vol. 3695, 1999.
  8. Shen, WM., et. al.  Building Integrated Robots for Soccer Competition. International Conference on Robotics and Automation, Belgium, 1998.
  9. Shen, WM., et. al. Distributed Robot Team Systems, International Conference on Multi Agent Systems, Paris, 1998.
  10. Shen, WM. and Bing Leng. Metapattern Generation for Integrated Data Mining. In the Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining, 1996.
  11. Leng, B. and WM. Shen. 1995. A Metapattern-Based Automated Discovery Loop. The KDD Workshop in the 4th International Conference on Deductive and Object-Oriented Databases, Singapore.
  12. Kero, B, L. Russell, S. Tsur and WM. Shen. 1995. An Overview of Data Mining Technologies. The KDD Workshop in the 4th International Conference on Deductive and Object-Oriented Databases, Singapore.
  13. Shen, WM., B. Mitbander, K.L. Ong, and C. Zaniolo. 1994. Using Metaqueries to Integrate Inductive Learning and Deductive Database Technology. AAAI Workshop on Knowledge Discovery from Databases. Seattle, OR.
  14. Shen, WM. (with M. Huhns, N. Jacobs, T. Ksiezyk, M. Singh, and P. Cannata). 1993. Integrating enterprise information models in Carnot. Proceedings of International Conference on Intelligent and Cooperative Information Systems. Rotterdam, Holland.
  15. Shen, WM. (with D. Woelk, P. Cannata, M. Huhns, and C. Tomlinson). 1993. Using Carnot for enterprise information integration. Proceedings of the Second International Conference on Parallel and Distributed Information Systems. 133-136. San Diego.
  16. Shen, WM. 1993. Learning finite state automata using local distinguishing experiments. Proceedings of Thirteenth International Joint Conference on Artificial Intelligence. Morgan Kaufmann.
  17. Saha, A and WM. Shen. 1993. A semi-stochastic algorithm for optimizing high dimensional functions . Proceedings of Ninth International Conference on Systems Engineering. Las Vegas University.
  18. Shen, WM. 1992. Complementary discrimination learning with decision lists. Proceedings of the Tenth National Conference on Artificial Intelligence. MIT Press.
  19. Shen, WM. 1992. Learning deterministic finite automata using local distinguishing experiments. Conference on Computational Learning Theory and Natural Learning Systems. MIT Press.
  20. Shen, WM. (with M. Huhns, N. Jacobs, T. Ksiezyk, M. Singh, and P. Cannata). 1992. Enterprise information modeling and model integration in Carnot. Enterprise Integration Modeling: Proceedings of the First International Conference. MIT Press.
  21. Shen, WM. (with D. Woelk, M. Huhns, and P. Cannata). 1992. Model driven enterprise information management in Carnot. Enterprise Integration Modeling: Proceedings of the First International Conference. MIT Press.
  22. Shen, WM. 1991. Discovering regularities from knowledge bases. Proceedings of the Eighth International Conference on Machine Learning. Morgan Kaufmann.
  23. Shen, WM. (with T.H. Chi and A.B. Whinston). 1991. AMOLS: An adaptive model learning system in a decision support system environment. Proceedings of Twenty-Fourth International Conference on System Science. IEEE Computer Society Press.
  24. Shen, WM. 1990. Complementary discrimination learning: a duality between generalization and discrimination. Proceedings of the Eighth National Conference on Artificial Intelligence. MIT Press.
  25. Shen, WM. and H. A. Simon. 1989. Rule creation and rule learning through environmental exploration. Proceedings of Eleventh International Joint Conference on Artificial Intelligence. Morgan Kaufmann.
  26. Shen, WM. 1988. Functional transformation and its application. Proceedings of Twenty-First International Conference on System Science. IEEE Computer Society Press.

PhD Dissertation

Shen, W-M. Learning from the Environment Based on Actions and Percepts, 1989.
Computer Science Department, Carnegie Mellon University, Supervisor Professor  Herbert A. Simon.
 

Technical Reports

  1. Shen, W-M., B. Leng, and A. Chatterjee. 1995. Applying the Metapattern Mechanism to Time Sequence Analysis. Technical Report, USC Information Sciences Institute, ISI/RR-95-398.
  2. Shen, W-M. (Editor) 1993. Learning Action Models. Technical report of Association of American Artificial Intelligence. AAAI Press.
  3. Shen, W-M. 1993. Learning finite state automata using local distinguishing experiments. MCC-Carnot-015-93. Microelectronics and Computer Technology Corporation, Austin, TX.
  4. Shen, W-M. 1993. Bayesian probability theory --- A general method for machine learning. MCC-Carnot-101-93. Microelectronics and Computer Technology Corporation, Austin, TX.
  5. Shen, W-M. 1993. Complementary discrimination learning with decision lists. MCC-Carnot-007-92. Microelectronics and Computer Technology Corporation, Austin, TX.
  6. Shen, W-M. (with C. Collet and M. Huhns). 1991. Resource integration without application modification. ACT-OODS-214-91. Microelectronics and Computer Technology Corporation, Austin, TX.
  7. Shen, W-M. (with C. Collet and M. Huhns). 1991. Resource integration using an existing large knowledge base. ACT-OODS-127-91. Microelectronics and Computer Technology Corporation, Austin, TX.
  8. Shen, W-M. 1990. Machine learning with the Cyc knowledge base. ACT-CYC-224-90. Microelectronics and Computer Technology Corporation, Austin, TX.
  9. Shen, W-M. 1987. Functional transformations in AI discovery systems. Technical Report CMU-CS-87-117, Carnegie Mellon University.
  10. Shen, W-M. 1987. Unsupervised learning of novel features from the environment. PhD Thesis Proposal, Computer Science Department, Carnegie Mellon University.
  11. Shen, W-M. 1987. An algorithm that infers novel features from the experiments. Technical Report, Computer Science Department, Carnegie Mellon University.