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Note: Links lead to the DBLP on the Web. Thomas R. Ioerger Dwi H. Widyantoro , Thomas R. Ioerger, John Yen : Tracking changes in user interests with a few relevance judgments. CIKM 2003 : 548-551 Dianxiang Xu , Michael S. Miller , Richard A. Volz , Thomas R. Ioerger: Collaborative Agents for C2 Teamwork Simulation. IC-AI 2003 : 723-729 Linli He , Thomas R. Ioerger: A Quantitative Model of Capabilities in Multi-Agent Systems. IC-AI 2003 : 730-736 R. Ganesh , Deborah A. Siegele , Thomas R. Ioerger: MOPAC: MOtif Finding by Preprocessing and Agglomerative Clustering from Microarrays. Pacific Symposium on Biocomputing 2003 : 41-52 Dianxiang Xu , Richard A. Volz , Thomas R. Ioerger, John Yen : Modeling and Analyzing Multi-Agent Behaviors Using Predicate/Transition Nets. International Journal of Software Engineering and Knowledge Engineering 13 (1): 103-124 (2003) Sen Cao , Richard A. Volz , Thomas R. Ioerger, Yu Zhang : Role-Based and Agent-Oriental Teamwork Modeling. IC-AI 2002 : 1190- Yu Zhang , Richard A. Volz , Thomas R. Ioerger, Sen Cao , John Yen : Proactive Information Exchange During Team Cooperation. IC-AI 2002 : 341-346 Dianxiang Xu , Richard A. Volz , Thomas R. Ioerger: Generating Parallel Based on Planning Graph Analysis of Predicate/Transition Nets. IC-AI 2002 : 440-446 Dwi H. Widyantoro , Thomas R. Ioerger, John Yen : An Incremental Approach to Building a Cluster Hierarchy. ICDM 2002 : 705-708 Dianxiang Xu , Richard A. Volz , Thomas R. Ioerger, John Yen : Modeling and verifying multi-agent behaviors using predicate/transition nets. SEKE 2002 : 193-200 J. Colby Johnson , Thomas R. Ioerger: A formal model of responsibilities in agent-based teams. Agents 2001 : 157-158 John Yen , Jianwen Yin , Thomas R. Ioerger, Michael S. Miller , Dianxiang Xu , Richard A. Volz : CAST: Collaborative Agents for Simulating Teamwork. IJCAI 2001 : 1135-1144 Keith E. Biggers , Thomas R. Ioerger: Automatic Generation of Communication and Teamwork within Multi-Agent Teams. Applied Artificial Intelligence 15 (10): 875-916 (2001) Dwi H. Widyantoro , Thomas R. Ioerger, John Yen : Learning user interest dynamics with a three-descriptor representation. JASIST 52 (3): 212-225 (2001) Kreshna Gopal , Thomas R. Ioerger: An Adaptive Planner Based on Learning of Planning Performance. AAAI/IAAI 2000 : 1073 Jianwen Yin , Michael S. Miller , Thomas R. Ioerger, John Yen , Richard A. Volz : A knowledge-based approach for designing intelligent team training systems. Agents 2000 : 427-434 Michael S. Miller , Jianwen Yin , Richard A. Volz , Thomas R. Ioerger, John Yen : Training Teams with Collaborative Agents. Intelligent Tutoring Systems 2000 : 63-72 Magy Seif El-Nasr , John Yen , Thomas R. Ioerger: FLAME-Fuzzy Logic Adaptive Model of Emotions. Autonomous Agents and Multi-Agent Systems 3 (3): 219-257 (2000) Thomas R. Ioerger: Detecting Feature Interactions from Accuracies of Random Feature Subsets. AAAI/IAAI 1999 : 350-357 Magy Seif El-Nasir , Thomas R. Ioerger, John Yen : PETEEI: A PET With Evolving Emotional Intelligence. Agents 1999 : 9-15 Magy Seif El-Nasr , Thomas R. Ioerger, John Yen , Donald H. House , Frederic I. Parke : Emotionally Expressive Agents. CA 1999 : 48-57 Dwi H. Widyantoro , Thomas R. Ioerger, John Yen : An Adaptive Algorithm for Learning Changes in User Interests. CIKM 1999 : 405-412 Thomas R. Ioerger, Thomas Holton , Jon A. Christopher , James C. Sacchettini : TEXTAL: A Pattern Recognition System for Interpreting Electron Density Maps. ISMB 1999 : 130-137 Thomas R. Ioerger: Integrating a Spatial Reasoner with a Resolution Theorem-Prover. AAAI/IAAI 1997 : 145-152 Thomas R. Ioerger: The Context-Dependence of Amino Acid Properties. ISMB 1997 : 157-166 Thomas R. Ioerger, Larry A. Rendell , Shankar Subramaniam : Searching for Representations to Improve Protein Sequence Fold-Class Prediction. Machine Learning 21 (1-2): 151-175 (1995) Thomas R. Ioerger: The Manipulation of Images to Handle Indeterminacy in Spatial Reasoning. Cognitive Science 18 (4): 551-593 (1994) Thomas R. Ioerger, Larry A. Rendell , Shankar Subramaniam : Constructive Induction and Protein Tertiary Structure Prediction. ISMB 1993 : 198-206 1 [ 16 ] 2 [ 22 ] [ 23 ] 3 [ 6 ] 4 [ 9 ] 5 [ 8 ] [ 11 ] 6 [ 25 ] 7 [ 14 ] 8 [ 26 ] 9 [ 6 ] 10 [ 8 ] 11 [ 18 ] 12 [ 12 ] [ 13 ] [ 17 ] [ 27 ] 13 [ 8 ] 14 [ 1 ] [ 3 ] 15 [ 6 ] 16 [ 25 ] 17 [ 1 ] [ 3 ] 18 [ 12 ] [ 13 ] [ 17 ] [ 19 ] [ 21 ] [ 22 ] [ 23 ] [ 24 ] [ 27 ] 19 [ 7 ] [ 15 ] [ 20 ] [ 28 ] 20 [ 17 ] [ 19 ] [ 21 ] [ 24 ] [ 27 ] 21 [ 7 ] [ 8 ] [ 9 ] [ 11 ] [ 12 ] [ 13 ] [ 15 ] [ 17 ] [ 19 ] [ 20 ] [ 22 ] [ 24 ] [ 28 ] 22 [ 12 ] [ 13 ] [ 17 ] 23 [ 22 ] [ 23 ]  ©2004 Association for Computing Machinery |
