Recent Publications

2008

• J. Kukluk, L. Holder, and D. Cook, Inference of edge replacement graph grammars, International Journal on Artificial Intelligence Tools, 2008.
• C. D. Corley, A. R. Mikler, D. Cook, and K. Singh, Dynamic intimate contact social networks and epidemic interventions, International Journal of Environmental and Healthcare Biotechnology, 2008.
• V. Jakkula and D. Cook, Anomaly detection using temporal data mining in a smart home environment, Methods of Information in Medicine, 2008.
• D. Brezeale and D. Cook, Automatic video classification: A survey of the literature, IEEE Transactions on Systems, Man, and Cybernetics, Part C, 2008.
• V. Jakkula and D. J. Cook, Enhancing smart home algorithms using temporal relations, Technology and Aging, IOS Press, 2008.
• V. Jakkula, A. Crandall, and D. J. Cook, Enhancing anomaly detection using temporal pattern discovery, Advanced Intelligent Environments, Springer, 2008.

2007

• D. Cook, L. Holder, and G. M. Youngblood, Graph-based analysis of human transfer learning using a game testbed, IEEE Transactions on Knowledge and Data Engineering, 19(11):1-14, 2007.
• K. Gopalratnam and D. Cook, Online sequential prediction via incremental parsing: The Active LeZi algorithm, IEEE Intelligent Systems, 22(1), 2007.
• J. Kukluk, L. Holder and D. J. Cook, Inference of node replacement graph grammars, Intelligent Data Analysis, 11(4), 2007.
• G. M. Youngblood and D. Cook, Data mining for hierarchical model creation, IEEE Transactions on Systems, Man, and Cybernetics, Part C, 37(4):561-572, 2007.
• D. Cook and S. K. Das, How smart are our environments? An updated look at the state of the art, Journal of Pervasive and Mobile Computing, 2007.
• D. Cook, Making sense of sensor data, IEEE Pervasive Computing, 2007.
• V. Jakkula and D. Cook, Prediction models for a smart home based health care system, Proceedings of the First International Workshop on Smart Homes for Tele-Health, 2007.
• V. Jakkula, A. Crandall, and D. Cook, Knowledge discovery in entity based smart environment resident data using temporal relations based data mining, Proceedings of the ICDM Workshop on Spatial and Spatio-Temporal Data Mining, 2007.
• J. Kukluk, L. Holder, and D. Cook, Inference of edge replacement graph grammars, Proceedings of the Florida Artificial Intelligence Research Symposium, 2007.
• C. Corley, L. Brown, A. Mikler, D. Cook, and K. Singh, Generating social networks of intimate contacts for the study of public health intervention strategies, Proceedings of the IEEE Seventh International Symposium on BioInformatics and BioEngineering, 2007.
• W. Davis, A. Kalyanaraman, and D. Cook, An information theoretic approach for the discovery of irregular and repetitive patterns in genomic data, Proceedings of the International Conference on Computational Systems Bioinformatics, 2007.
• V. Jakkula and D. Cook, Mining sensor data in smart environments for temporal activity predition, Proceedings of the First International Workshop on Knowledge Discovery from Sensor Data, 2007.
• J. Kukluk, L. Holder, and D. Cook, Inference of node and edge replacement graph grammars, Proceedings of the ICML Workshop on Challenges and Applications of Grammar Induction, 2007.
• V. Jakkula and D. Cook, Temporal pattern discovery for anomaly detection in smart homes, Proceedings of the International Conference on Intelligent Environments, 2007.
• V. Jakkula and D. Cook, Using temporal relations in smart home data for activity prediction, Proceedings of the ICML Workshop on the Induction of Process Models, 2007.
• J. Kukluk, C. You, L. Holder and D. Cook, Learning node replacement graph grammars in metabolic pathways, International Conference on Bioinformatics and Computational Biology, 2007.
• V. Jakkula and D. Cook, Learning temporal relations in smart home data, Proceedings of the Second International Conference on Technology and Aging, 2007.
• V. Jakkula and D. Cook, Prediction models for a smart home based health care system, Proceedings of the First International Workshop on Smart Homes for Tele-Health, 2007.
• P. Rashidi, G. M. Youngblood, D. Cook, and S. Das, Inhabitant guidance of smart environments, Proceedings of the International Conference on Human-Computer Interaction, 2007.
• D. J. Cook, G. M. Youngblood, and G. Jain, Algorithms for smart spaces, The Engineering Handbook on Smart Technology for Aging, Disability and Independence, A. Helal, M. Mokhtari and B. Abdulrazak, Editors, John Wiley and Sons, 2007.

2006

• D. Cook and L. Holder (eds.), Mining Graph Data, John Wiley and Sons, December 2006.

• D. Cook, Health Monitoring and Assistance to Support Aging in Place, Journal of Universal Computer Science, 12(1), pages 15-29, 2006.
• J. Coble, D. Cook, and L. Holder, Structure Discovery in Sequentially-Connected Data Streams, International Journal on Artificial Intelligence Tools, 2006.

• N. Ketkar, L. Holder, and D. Cook, Mining in the Proximity of Subgraphs, Proceedings of LinkKDD, 2006.
• C. D. Corley, D. Cook, L. Holder, and K. P. Singh, Graph-based data mining in epidemia and terrorism data, Proceedings of the Conference on Quantitative Methods and Statistical Applications in Defense and National Security, 2006.
• C.-C Tseng and D. Cook, Mining From Time Series Human Movement Data, Proceedings of the Conference on Systems, Man, and Cybernetics, 2006.
• V. Jakkula, M. Youngblood, and D. Cook, Identification of Lifestyle Behavior Patterns with Prediction of the Happiness of an Inhabitant in a Smart Home, Proceedings of the AAAI Workshop on Computational Aesthetics, 2006.
• G. Jain, D. Cook, and V. Jakkula, Monitoring health by detecting drifts and outliers for a smart environment inhabitant, Proceedings of the International Conference On Smart Homes and Health Telematics, 2006.
• J. Kukluk, L. Holder and D. Cook, Inference of node replacement recursive graph grammars, Proceedings of the SIAM Conference on Data Mining, April 2006.
• S. Das and D. Cook, Designing and Modeling Smart Environments, Proceedings of the Workshop on Autonomic Computing and Communications, 2006.
• K. Ates, J. Kukluk, L. Holder, D. Cook and K. Zhang, Graph Grammar Induction on Structural Data for Visual Programming, Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence, November 2006.
• J. Kukluk, C. You, L. Holder and D. Cook, Discovering Recursive Patterns in Biological Networks Dallas Area Bioinformatics and Computational Biology Workshop, August 2006.
• D. Brezeale and D. Cook, Using Closed Caption and Visual Features to Classify Movies by Genre, Proceedings of the KDD/MDM Workshop, 2006.
• J. Potts, D. Cook, and L. Holder, Learning from Supervised Graphs, Applied Graph Theory in Computer Vision and Pattern Recognition (M. Last, A. Kandel, and H. Bunke, editors), Wiley, 2006.
• D. Cook, G. M. Youngblood, and G. Jain, Algorithms for Smart Spaces, Technology for Aging, Disability and Independence: Computer and Engineering for Design and Applications, Wiley, 2006.
• D. Cook, G. M. Youngblood, and S. K. Das, A Multi-Agent Approach to Controlling a Smart Environment, AI and Smart Homes, pages 165-182, Springer Verlag, 2006.
• S. K. Das and D. Cook, Smart Home Environments: A Paradigm Based on Learning and Prediction, Wireless Mobile and Sensor Networks: Technology, Applications and Future Directions, (R. Shorey, A. Ananda, M. C. Chan, and W. T. Ooi, eds.), pages 337-356, Wiley, 2006.

2005

• S. Bandyopadhyay, U. Maulik, L. Holder and D. Cook (eds.), Advanced Methods for Knowledge Discovery from Complex Data, Springer, 2005.

• L. Holder, D. Cook, J. Coble and M. Mukherjee, Graph-based Relational Learning with Application to Security, Fundamenta Informaticae Special Issue on Mining Graphs, Trees and Sequences, 66(1-2):83-101, 2005.
• M. Youngblood, D. Cook, and L. Holder, Managing Adaptive Versatile Environments, Journal of Pervasive and Mobile Computing, 2005.
• J. Kukluk, L. Holder, and D. Cook, Algorithm and Experiments in Testing Planar Graphs for Isomorphism, Journal of Graph Algorithms and Applications, 8(3), 2005.
• J. Coble, D. Cook, R. Rathi, and L. Holder, Iterative Structure Discovery in Graph-Based Data, International Journal of Artificial Intelligence Techniques, 14(1-2), 2005.
• N. Ketkar, L. Holder, and D. Cook, Comparison of Graph-based and Logic-based Multi-Relational Data Mining, SIGKDD Explorations Special issue on Link Mining 7(2), 2005.

• J. Coble and D. Cook, Structure Discovery in Sequentially Connected Data, Proceedings of the Florida Artificial Intelligence Research Symposium, 2005. Recipient of the best paper award.
• K. Gee and D. Cook, Text Classification Using Graph-Encoded Linguistic Elements, Proceedings of the Florida Artificial Intelligence Research Symposium, 2005.
• R. Rathi and D. Cook, A Serial Partitioning Approach to Scaling Graph-Based Knowledge Discovery, Proceedings of the Florida Artificial Intelligence Research Symposium, 2005.
• J. Potts, D. Cook, and L. Holder, Learning from Examples in a Single Graphs, Proceedings of the Florida Artificial Intelligence Research Symposium, 2005.
• M. Youngblood, D. Cook, and L. Holder, Managing Adaptive Versatile Environments, Proceedings of the IEEE International Conference on Pervasive Computing and Communications, 2005.
• N. Ketkar, L. Holder and D. Cook, Qualitative Comparison of Graph-based and Logic-based Multi-Relational Data Mining: A Case Study, Proceedings of the ACM KDD Workshop on Multi-Relational Data Mining, August 2005.
• N. Ketkar, L. Holder, D. Cook, R. Shah and J. Coble, Subdue: Compression-based Frequent Pattern Discovery in Graph Data, Proceedings of the ACM KDD Workshop on Open-Source Data Mining, August 2005.
• S. K. Das and D. Cook, Designing Smart Environments: A Paradigm Based on Learning and Prediction, Proceedings of First International Conference on Pattern Recognition and Machine Intelligence (PReMI'05), Kolkata, India, Dec 18-22, 2005.
• M. Youngblood, D. Cook, L. Holder and E. Heierman, Automation Intelligence for the Smart Environment, Proceedings of the International Joint Conference on Artificial Intelligence, 2005.
• J. Potts, L. Holder, D. Cook, and J. Coble, Learning Concepts from Intelligence Data Embedded in a Supervised Graph, Proceedings of the International Conference on Intelligence Analysis, 2005.
• M. Youngblood, L. Holder, and D. Cook, A Learning Architecture for Automating the Intelligent Environment, Proceedings of the Conference on Innovative Applications of Artificial Intelligence, 2005.

• L. Holder and D. Cook, Graph-based Data Mining, J. Wang (ed.), Encyclopedia of Data Warehousing and Mining, Idea Group Publishing, 2005.
• S. K. Das and D. Cook, Smart Home Environments: A Paradigm Based on Learning and Prediction, Wireless Mobile and Sensor Networks, Wiley, 2005.
• D. Cook, L. Holder, J. Coble and J. Potts, Graph-based Mining of Complex Data, S. Bandyopadhyay, U. Maulik, L. Holder and D. Cook (eds.), Advanced Methods for Knowledge Discovery from Complex Data, Springer, 2005.

2004

• Smart Environments: Technologies, Protocols and Applications (D. Cook and S. Das, editors), John Wiley and Sons.

• K. Gopalratnam and D. Cook, Active LeZi: An Incremental Parsing Algorithm for Sequential Prediction, International Journal of Artificial Intelligence Tools, 14(1-2), pages 917-930, 2004.
• D. Cook and S. Das, MavHome: Work in Progress, IEEE Pervasive Computing, 2004.
• D. Cook, L. Holder, M. Huber, and R. Yerraballi, Enhancing Computer Science Education with a Wireless Intelligent Simulation Environment, Journal of Computing in Higher Education, 16(1), 2004.
• J. Coble, D. Cook, L. Holder, and R. Rathi, Structure Discovery from Sequential Data, Proceedings of the Florida Artificial Intelligence Research Symposium, 2004. Extended paper in International Journal of Artificial Intelligence Techniques, 14(1-2), 2005.
• A. Rakhshan, L. Holder and D. Cook, Structural Web Search Engine, International Journal of Artificial Intelligence Tools, 13(1), pages 27-33, 2004.
• I. Jonyer, L. Holder and D. Cook, MDL-Based Context-Free Graph Grammar Induction and Applications, International Journal of Artificial Intelligence Tools, 13(1), pages 45-64, 2004.
• S. Rao and D. Cook, Predicting Inhabitant Actions Using Action and Task Models with Application to Smart Homes, International Journal of Artificial Intelligence Tools, 13(1), pages 81-100, 2004.

• S. Das and D. Cook, Health Monitoring in an Agent-Based Smart Home, Proceedings of the International Conference on Smart Homes and Health Telematics (ICOST), Singapore, September, 2004.
• E. Heierman, M. Youngblood, and D. Cook, Mining Temporal Sequences to Discover Interesting Patterns, KDD Workshop on Mining Temporal and Sequential Data, 2004.
• I. Jonyer, L. Holder, and D. Cook, Attribute-Value Selection Based on the Minimum Description Length, Proceedings of the International Conference on Artificial Intelligence, 2004.

• S. Das and D. Cook, Smart Home Environments: A Paradigm Based on Learning and Prediction, Wireless Mobile and Sensor Networks, Wiley, 2004.
• L. Holder and D. Cook, Graph-based Data Mining, Encyclopedia of Data Warehousing and Mining, 2004.
• D. Cook and M. Youngblood, Smart Homes, Encyclopedia of Human-Computer Interaction, 2004.
• S. K. Das and D. Cook, Health Monitoring in an Agent-Based Smart Home by Activity Prediction, in Toward a Human-Friendly Assistive Environment, D. Zhang and M. Mokhari (eds.), IOS Press, pages 3-14, 2004.

2003

• L. Holder and D. Cook, Graph-Based Relational Learning: Current and Future Directions, SIGKDD Explorations special issue on Multirelational Data Mining, 5(1), pages 90-93, 2003.
• D. Cook, N. Manocha, and L. Holder, Using a Graph-Based Data Mining System to Perform Web Search, International Journal of Pattern Recognition and Artificial Intelligence, 2003.
• P. Sandanayake and D. Cook, Imitating Agent Game Strategies Using a Scalable Markov Model, International Journal of Pattern Recognition and Artificial Intelligence, 2003.
• G. Peterson and D. Cook, Incorporating Decision-Theoretic Planning in a Robot Architecture, Robotics and Autonomous Systems, 42(2), pages 89-106, 2003.

• D. Cook, S. Das, Karthik Gopalratnam, and Abhishek Roy, Health Monitoring in an Agent-Based Smart Home, Proceedings of the International Conference on Aging, Disability and Independence Advancing Technology and Services to Promote Quality of Life, 2003.
• E. Heierman and D. Cook, Improving Home Automation by Discovering Regularly Occurring Device Usage Patterns, Proceedings of the International Conference on Data Mining, 2003. % 128 papers selected from 501
• Y. Wang, D. Cook, V. Papudesi, and M. Huber, User-Guided Reinforcement Learning of Robot Assistive Tasks for an Intelligent Environment, Proceedings of the Conference on Intelligent Robots and Systems, 2003. % 620 papers selected from 1042
• S. Rao and D. Cook, Identifying Tasks and Predicting Actions in Smart Homes using Unlabeled Data, Proceedings of the Machine Learning Workshop on The Continuum from Labeled to Unlabeled Data, 2003.
• C. Noble and D. Cook, Graph-Based Anomaly Detection, Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2003.
• F. Khawaja, D. Gjoni, M. Huber, D. Cook and M. Youngblood, Achieving Faster Convergence to the Optimal Policy by Using Knowledge of the Reward Structure, Proceedings of the Artificial Intelligence Applications Conference, 2003.
• I. Jonyer, L. Holder, and D. Cook, MDL-Based Context-Free Graph Grammar Induction, Proceedings of the Sixteenth International Conference of the Florida AI Research Society, May 2003.
• A. Rakhshan, L. Holder, and D. Cook, Structural Web Search Engine, Proceedings of the Sixteenth International Conference of the Florida AI Research Society, May 2003.
• K. Gopalratnam and D. Cook, Active LeZi: An Incremental Parsing Algorithm for Device Usage Prediction in the Smart Home, Proceedings of the Florida Artificial Intelligence Research Symposium, 2003.
• R. Mehta, D. Cook, and L. Holder, Identifying Inhabitants of an Intelligent Environment using a Graph-Based Data Mining Systems, Proceedings of the Florida Artificial Intelligence Research Symposium, 2003.
• S. Rao and D. Cook, Improving the Performance of Action Prediction through Identification of Abstract Tasks, Proceedings of the Florida Artificial Intelligence Research Symposium, 2003.
• V. Papudesi, M. Huber, Y. Wang, and D. Cook, Integrating User Commands and Autonomous Task Performance in a Reinforcement Learning Framework, Proceedings of the AAAI Spring Symposium on Human Interaction with Autonomous Systems in Complex Environments, 2003.
• D. Cook, M. Youngblood, E. Heierman, K. Gopalratnam, S. Rao, A. Litvin, and F. Khawaja, MavHome: An Agent-Based Smart Home, Proceedings of the Conference on Pervasive Computing, 2003.
• A. Roy, S. Bhaumik, A. Bhattacharya, K. Basu, D. Cook, and S. Das, Location Aware Resource Management in Smart Homes, Proceedings of the Conference on Pervasive Computing, 2003.
• K. Gee and D. Cook, Using Latent Semantic Indexing to Filter Spam, ACM Symposium on Applied Computing, Data Mining Track, 2003.

2002

• S. K. Das, D. Cook, A. Bhattacharya, E. O. Heierman, III, and T.-Y. Lin, The Role of Prediction Algorithms in the MavHome Smart Home Architecture, IEEE Wireless Communications Communications Special Issue on Smart Homes, 9(6), pages 77-84, 2002.
• J. Ramirez, D. Cook, L. Peterson, and D. Peterson, Temporal Pattern Discovery in Course-of-Disease Data, IEEE Engineering in Medicine and Biology.
• W. Harris, D. Cook, and F. Lewis, A Matrix Formulation for Integration of Planning and Manufacturing, Journal of Intelligent Manufacturing.

• I. Jonyer, L. Holder, and D. Cook, Concept Formation Using Graph Grammars, Proceedings of the KDD Workshop on Multi-Relational Data Mining, 2002.
• J. Gonzalez, L. Holder, and D. Cook, Experimental Comparison of Graph-Based Relational Concept Learning with Inductive Logic Programming Systems, Proceedings of the Inductive Logic Programming Conference, 2002.
• J. Gonzalez, L. Holder, and D. Cook, Graph-Based Relational Concept Learning, Proceedings of the International Machine Learning Conference, 2002.
• S. Bandyopadhyay, U. Maulik, D. Cook, L. Holder, and Y. Ajmerwala, Enhancing Structure Discovery for Data Mining in Graphical Databases Using Evolutionary Programming, Proceedings of the Florida Artificial Intelligence Research Symposium, pages 232-236, 2002.
• P. Sandanayake and D. Cook, Imitating Agent Game Strategies Using a Scalable Markov Model, Proceedings of the Florida Artificial Intelligence Research Symposium, 2002.

• L. Holder, D. Cook, J. Gonzalez, and I. Jonyer, Structural Pattern Recognition in Graphs, Pattern Recognition and String Matching (D. Chen and X. Cheng, eds.), Kluwer Academic Publishers, 2002.

2001

• I. Jonyer, D. Cook, and L. Holder, Discovery and Evaluation of Graph-Based Hierarchical Conceptual Clusters, Journal of Machine Learning Research, 2, pages 19-43, 2001.
• D. Cook, L. Holder, S. Su, R. Maglothin, and I. Jonyer, Structural Mining of Molecular Biology Data, IEEE Engineering in Medicine and Biology special issue on Advances in Genomics, 20(4), pages 67-74, 2001.
• I. Jonyer, L. Holder, and D. Cook, Hierarchical Conceptual Structural Clustering, International Journal on Artificial Intelligence Tools, 10(1-2), pages 107-136, 2001.
• L. Holder and D. Cook, An Integrated Tool for Enhancement of Artificial Intelligence Curriculum, Journal of Computing in Higher Education, 12(2), 2001.
• D. Cook, L. Holder, G. Galal, and R. Maglothin, Approaches to Parallel Graph-Based Knowledge Discovery, Journal of Parallel and Distributed Computing, 61(3), pages 427-446, 2001.
• J. Ramirez, D. Cook, L. L. Peterson, and D. M. Peterson, Temporal Pattern Discovery in Sparse Course-of-Disease Data, Medical Data Mining and Knowledge Discovery (K.J. Cios, ed.), Springer-Verlag, 2001.

• J. Gonzalez, L. Holder, and D. Cook, Application of Graph-Based Concept Learning to the Predictive Toxicology Domain, Proceedings of the Predictive Toxicology Challenge Workshop, 2001.
• N. Manocha, D. Cook, and L. Holder, Structural Web Search Using a Graph-Based Discovery System, Proceedings of the Florida Artificial Intelligence Research Symposium, 2001.
• D. Cook and L. Holder, A Client-Server Interactive Tool for Integrated Artificial Intelligence Curriculum, Proceedings of the FLAIRS Special Track on AI Education, 2001.
• J. R. Nayak and D. Cook, Approximate Association Rule Mining, Proceedings of the Florida Artificial Intelligence Research Symposium, 2001.
• J. Gonzalez, L. Holder, and D. Cook, Graph-Based Concept Learning, Proceedings of the Florida Artificial Intelligence Research Symposium, 2001.
• C. Hannon and D. Cook, Exploring the Use of Cognitive Models in AI Applications Using the Stroop Effect, Proceedings of the Florida Artificial Intelligence Research Symposium, 2001.

2000

• D. Cook and L. Holder, Graph-Based Data Mining, IEEE Intelligent Systems, 15(2), pages 32-41, 2000.
• W. Harris and D. Cook, Automatically Generating Plans for Manufacturing, Journal of Intelligent Systems, 10(3), pages 297-319, 2000.
• J. Ramirez, D. Cook, L. L. Peterson, and D. M. Peterson, An Event Set Approach to Sequence Discovery in Medical Data, Intelligent Data Analysis, 4(6), pages 513-530, 2000.

• J. Gonzalez, L. Holder, and D. Cook, Graph-Based Concept Learning, Proceedings of the National Conference on Artificial Intelligence, 2000.
• I. Jonyer, L. Holder, and D. Cook, Graph-Based Hierarchical Conceptual Clustering in Structural Data, Proceedings of the National Conference on Artificial Intelligence, 2000.
• W. Harris, D. Cook, and F. Lewis, Combining Representations from Manufacturing, Machine Planning, and Manufacturing Resource Planning, Proceedings of the AAAI Workshop on Representational Issues for Real-World Planning Systems, 2000.
• J. Gonzalez, I. Jonyer, L. Holder and D. Cook, Efficient Mining of Graph-Based Data, Proceedings of the AAAI Workshop on Learning Statistical Models from Relational Data, 2000.
• G. Peterson and D. Cook, Decision-Theoretic Planning in the Graphplan Framework, Proceedings of the Artificial Intelligence Planning Symposium, 2000.
• A. Baritchi and D. Cook, Discovering Structural Patterns in Telecommunications Data, Proceedings of the Florida AI Research Symposium, pages 82-85, 2000.
• J. Gonzalez, L. Holder, and D. Cook, Structural Knowledge Discovery Used to Analyze Earthquake Activity, Proceedings of the Florida AI Research Symposium, pages 86-90, 2000.
• C. Hannon and D. Cook, A Parallel Approach to Unified Cognitive Modeling of Language, Proceedings of the Thirteenth Canadian Conference on Artificial Intelligence, 2000.
• C. Hannon and D. Cook, A Parallel Approach to Modeling Language Learning and Understanding in Young Children, Proceedings of the Florida AI Research Symposium, pages 209-213, 2000.
• J. Coble and D. Cook, Real-time Learning when Concepts Shift, Proceedings of the Florida AI Research Symposium, pages 192-196, 2000.
• I. Jonyer, L. Holder, and D. Cook, Graph-Based Hierarchical Conceptual Clustering, Proceedings of the Florida AI Research Symposium, pages 91-95, 2000.

1999

• D. Cook and R.C. Varnell, Adaptive Parallel Iterative Deepening Search, Journal of Artificial Intelligence Research, volume 9, pages 167-194, 1999.
• S. Su, D. Cook, and L. Holder, Knowledge Discovery in Molecular Biology: Identifying Structural Regularities in Proteins, Intelligent Data Analysis, volume 3, pages 413-436, 1999.
• G. Galal, D. Cook, and L. Holder, Exploiting Parallelism in a Scientific Discovery System to Improve Scalability, Journal of the American Society for Information Science, 50(1), pages 65-73, 1999.
• K.S. Tae, D. Cook, and L. Holder, Experimentation-Driven Knowledge Acquisition for Planning, Computational Intelligence, 15(3), 1999.
• D. Cook, Preface to the FLAIRS Special Issue, International Journal of Pattern Recognition and Artificial Intelligence, 13(2), pages 1-2, 1999.

• P. Gmytrasiewicz, C.-C. Tseng, and D. Cook, Optimization of Parallel Search Using ML and Uncertain Reasoning, Proceedings of the IJCAI Workshop on Statistical Machine Learning for Large-Scale Optimization, 1999.
• G. Peterson and D. Cook, Decision-Theoretic Layered Robotic Control Architecture, Proceedings of the National Conference on Artificial Intelligence, 1999.
• R. Chittimoori, L. Holder, and D. Cook, Applying the Subdue Substructure Discovery System to the Chemical Toxicity Domain, Proceedings of the Florida AI Research Symposium, 1999.
• D. Cook and P. Gmytrasiewicz, Controlling the Parameters of Parallel Search Using Uncertainty Reasoning, Proceedings of the AAAI Symposium on Search Strategy under Uncertain and Incomplete Information, 1999.
• R. Chittimoori, L. Holder, and D. Cook, Applying the Subdue Substructure Discovery System to the Chemical Toxicity Domain, Proceedings of the AAAI Spring Symposium on Predictive Toxicology of Chemicals: Experiences and Impact of AI Tools, 1999.
• J. Coble and D. Cook, Virtual Environments: An Agent-Based Approach, Proceedings of the AAAI Spring Symposium on Agents with Adjustable Autonomy, 1999.
• J. Coble and D. Cook, Virtual Environments: An Agent-Based Approach, Proceedings of the AAAI Spring Symposium on Intelligent Agents in Cyberspace, 1999.
• D. Cook and C. Hannon, Adaptive parallel search for theorem proving, Proceedings of the Florida AI Research Symposium, 1999.
• W. Briggs and D. Cook, Anytime planning for optimal tradeoff between deliberative and reactive planning, Proceedings of the Florida AI Research Symposium, 1999.
• S. Su, D. Cook, and L. Holder, Application of Knowledge Discovery to Molecular Biology: Identifying Structural Regularities in Proteins, Proceedings of the Pacific Symposium on Biocomputing, 1999.

• D. Cook, G. Galal, and L. Holder, Improving Scalability of Scientific Discovery Systems by Exploiting Parallelism, in Pattern Discovery in Biological Data: Tools, Techniques and Application, J. Wang, B. Shapiro, and D. Shasha (eds.), Oxford University Press, 1999.

1998

• W. Harris, F. Lewis, and D. Cook, Machine Planning for Manufacturing, Journal of Intelligent Manufacturing, 9(5), pages 413-430, 1998.

• J. Coble and D. Cook, Fault Tolerant Coordination of Robot Teams, Proceedings of the AAAI Fall Symposium on Cognitive Robotics, 1998.
• G. Peterson and D. Cook, Learning and Planning in a Robotic Game, Proceedings of the AAAI Fall Symposium on Integrated Planning for Autonomous Agent Architectures, 1998.
• W. Harris and D. Cook, Machine Planning to Design Manufacturing Processes, Proceedings of the AAAI Fall Symposium on Integrated Planning for Autonomous Agent Architectures, 1998.
• S. Whisenhunt and D. Cook, Comparison of Techniques to Learn Agent Strategies in Adversarial Games, Proceedings of the Machine Learning Workshop on the Methodology of Applying Machine Learning, 1998.
• S. Taylor, D. Levine, K. Kavi, and D. Cook, A comparison of multithreading implementations*, Yale Multithreaded Programming Workshop, 1998.
• L. Holder and D. Cook, Coupling two complementary knowledge discovery systems, Proceedings of the Florida AI Research Symposium, 1998.
• W. Harris and D. Cook, Integrating hierarchical and analogical planning, Proceedings of the Florida AI Research Symposium, 1998.
• R. C. Varnell and D. Cook, Integrating machine learning in parallel heuristic search, Proceedings of the Florida AI Research Symposium, 1998.
• G. Peterson and D. Cook, DFA learning of opponent strategies, Proceedings of the Florida AI Research Symposium, 1998.
• D. Cook, G. Galal, and L. Holder, Exploiting Parallelism in Knowledge Discovery Systems to Improve Scalability, Proceedings of the Thirty-First Hawaii International Conference on System Sciences, 1998.

• D. Cook, G. Galal, and L. Holder, Improving Scalability of Scientific Discovery Systems by Exploiting Parallelism, Pattern Discovery in Biological Data: Tools, Techniques and Application, Oxford University Press, 1998.

1997

• S. Djoko, D. Cook, and L. Holder, An Empirical Study of Domain Knowledge and its Benefits to Substructure Discovery, IEEE Transactions on Knowledge and Data Engineering, 9(4), 1997.

• D. Cook and R. C. Varnell, Maximizing the Benefits of Parallel Search Using Machine Learning, Proceedings of the National Conference on Artificial Intelligence, 1997.
• G. Galal, D. Cook and L. Holder, Improving Scalability in a Scientific Discovery System by Exploiting Parallelism, Proceedings of the International Conference on Knowledge Discovery and Data Mining, 1997.
• G. Galal and D. Cook, Exploiting Parallelism in a Scientific Discovery System to Improve Scalability, Proceedings of the Tenth Annual Florida AI Research Symposium, 1997.
• D. Cook, Improving the Performance of Planning Systems Using Parallel Hardware and Flexible Social Laws, Proceedings of the NSF Design and Manufacturing Grantees Conference, 1997.

• D. Cook, A Hybrid Approach to Improving the Performance of Parallel Search, in Parallel Processing for Artificial Intelligence, J. Geller (ed.), Elsevier Science Publishers, 1997.
• E. Mettala, D. Cook and K. Harbison, Scenario-Based Design of UGV RSTA Algorithms, in Reconnaissance, Surveillance, and Target Acquisition for the Unmanned Ground Vehicle, O. Firschein and T. Strat (eds.), 1997.
• D. Cook, P. Gmytrasiewicz and L. Holder, Decision-Theoretic Multi-Agent Cooperative Sensor Planning, in Reconnaissance, Surveillance, and Target Acquisition for the Unmanned Ground Vehicle, O. Firschein and T. Strat (eds.), 1997.

1996

• D. Cook, P. Gmystrasiewicz and L. Holder, Decision-Theoretic Cooperative Sensor Planning, IEEE Transactions on Pattern Analysis and Machine Intelligence, 18(18), 1996.
• D. Cook, L. Holder, and S. Djoko, Scalable Discovery of Informative Structural Concepts Using Domain Knowledge, IEEE Expert, 10, pages 59-68, 1996.

• D. Cook, P. Gmytrasiewicz and L. Holder, Multi-Agent Cooperative Sensor Planning, Proceedings of the Image Understanding Workshop, 1321-1332, 1996.
• E. Mettala, D. Cook, and K. Harbison, Application of the Scenario-Based Engineering Process to the Unmanned Ground Vehicle Project, Proceedings of the Image Understanding Workshop, 627-641, 1996.
• K. S. Tae and D. Cook, Experimental knowledge acquisition for planning, Proceedings of the Conference on Machine Learning, 1996.
• W. Briggs and D. Cook, A Clustering Approach to Resource Allocation in Multiagent Systems, Proceedings of the Florida AI Research Symposium, pages 127-131, 1996.
• R. C. Varnell, D. Cook, and L. Peterson, Optimizing the Performance of Parallel Heuristic Search, Proceedings of the Florida AI Research Symposium, pages 385-389, 1996.
• K. S. Tae and D. Cook, Experimentation-Driven Incremental Operator Learning, Proceedings of the Florida AI Research Symposium, pages 204-208, 1996.
• D. Cook, Scaling up Planning Systems Using Parallel Hardware and Machine Learning, Proceedings of the NSF Design and Manufacturing Grantees Conference, 1996.
• K. S. Tae and D. Cook, Knowledge Acquisition for Planning with Incomplete Information, Proceedings of the AAAI Spring Symposium on Planning with Incomplete Information for Robot Problems, 1996.

1995

• K. Woods, D. Cook, L. O. Hall, K. W. Bowyer, and L. Stark, Learning Combination of Evidence Functions in Object Recognition, Journal of Artificial Intelligence Research, 3, 187-222, 1995.
• D. Cook and L. Holder, Knowledge Discovery from Structural Data, Journal of Intelligence and Information Sciences, 5(3), 229-245, 1995.

• W. Briggs and D. Cook, Flexible Social Laws, Proceedings of the International Joint Conference on Artificial Intelligence, 1995.
• S. Djoko, D. Cook, and L. Holder, Analyzing the Benefits of Domain Knowledge in Substructure Discovery, Proceedings of the First International Conference on Knowledge Discovery and Data Mining (KDD-95), 1995.
• J. Baumgartner, D. Cook, and B. Shirazi, Genetic Solutions to the Load Balancing Problem, Proceedings of the International Conference on Parallel Processing, 1995.
• S. Nerur and D. Cook, Maximizing the Speedup of Parallel Search Using HyPS, Proceedings of the Third International Workshop on Parallel Processing for Artificial Intelligence, 1995.

• L. Stark, K. W. Bowyer, K. Woods, L. Hall, and D. Cook, Application of learning techniques in a function-based recognition system, Symbolic Visual Learning, K. Ikeuchi and M. Veloso (eds.), Oxford University Press, 1995.