Publications

Here's a partial list of my publications (for example, it doesn't include workshop papers and the like; however, you can find at least some of those here). It probably isn't up-to-date, but I do feel guilty about that. On the other hand, at least now it's cute and automated. It required hacking someone else's perl code, stringing together and modifying three different code bases, and dealing with a file length feature in NFS, but I got tenure, and--who knows?--maybe that's what made the difference.

BTW, where I've provided PDFs, I should point out that they are usually copyright the publisher, something about only for academic use, something else legal, etc.


Year:   Author:
Topic:   Venue:
Show topics?

David Roberts and Charles L. Isbell. Lessons on Using Computationally Generated Influence for Shaping Narrative Experiences. To appear in Transactions on Computational Intelligence and AI in Games, 2014.
      Abstract, BibTeX, Topics: autonomous agents; computational influence; drama management

Jonathan Scholz, Martin Levihn, Charles L. Isbell, and David Wingate. A Physics-Based Model Prior for Object-Oriented MDPs. In Proceedings of the 31st International Conference on Machine Learning (ICML), 2014.
      BibTeX, Topic: reinforcement learning

Joshua Jones and Charles L. Isbell. Story Similarity Measures for Drama Management with TTD-MDPs. In Proceedings of the 13th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2014.
      BibTeX, Topics: autonomous agents; drama management; ttd-mdps

Shane Griffith, Kaushik Subramanian, Jonathan Scholz, Charles L. Isbell, and Andrea Thomaz. Policy Shaping: Integrating Human Feedback with Reinforcement Learning. In Advances in Neural Information Processing Systems (NIPS) 26, 2013.
      BibTeX, Topics: interactive machine learning; reinforcement learning; human teaching; policy shaping

Liam Mac Dermed and Charles L. Isbell. Point Based Value Iteration with Optimal Belief Compression for Dec-POMDPs. In Advances in Neural Information Processing Systems (NIPS) 26, 2013.
      Abstract, PDF, BibTeX, Topics: reinforcement learning; multi-agent reinforcement learning; game theory

Ryan Curtin, William March, Parikshit Ram, David Anderson, Alexander Gray, and Charles L. Isbell. Tree-Independent Dual-Tree Algorithms. In Proceedings of the Thirtieth International Conference on Machine Learning (ICML), 2013.
      Abstract, PDF, BibTeX, Topic: scalable machine learning

Luis Carlos Cobo Rus, Charles L. Isbell, and Andrea Thomaz. Object Focused Q-learning for Autonomous Agents. In Proceedings of the Twelfth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2013.
      Abstract, PDF, BibTeX, Topics: interactive machine learning; reinforcement learning; human teaching

Joshua Letchford, Liam Mac Dermed, Vincent Conitzer, Ronald Parr, and Charles L. Isbell. Computing Optimal Strategies to Commit to in Stochastic Games. In Proceedings of the Twenty-Sixth National Conference on Artificial Intelligence (AAAI), 2012.
      Abstract, PDF, BibTeX, Topics: reinforcement learning; multi-agent reinforcement learning; game theory

Luis Carlos Cobo Rus, Charles L. Isbell, and Andrea Thomaz. Automatic Decomposition and State Abstraction from Demonstration. In Proceedings of the Eleventh International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2012.
      Abstract, PDF, BibTeX, Topics: interactive machine learning; reinforcement learning; human teaching

Karthik Narayan, Charles L. Isbell, and David Roberts. DEXTOR: Reduced Effort Authoring for Template-Based Natural Language Generation. In Proceedings of the Seventh Artificial Intelligence and Interactive Digital Entertainment (AIIDE), 2011.
      Abstract, PDF, BibTeX, Topics: entertainment; autonomous agents; natural language generation

Liam Mac Dermed, Karthik Narayan, Charles L. Isbell, and Lora Weiss. Quick Polytope Approximation of All Correlated Equilibria in Stochastic Games. In Proceedings of the Twenty-Sixth National Conference on Artificial Intelligence (AAAI), 2011.
      Abstract, PDF, BibTeX, Topics: reinforcement learning; multi-agent reinforcement learning; game theory

Luis Carlos Cobo Rus, Peng Zang, Charles L. Isbell, and Andrea Thomaz. Automatic State Abstraction from Demonstration. In Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence (IJCAI), 2011.
      Abstract, PDF, BibTeX, Topics: reinforcement learning; human teaching

Michael Holmes, Alexander Gray, and Charles L. Isbell. Fast Kernel Conditional Density Estimation: A Dual Tree Monte Carlo Approach. Computational Statistics and Data Analysis, 54(7):1707-1718, 2010.
      Abstract, BibTeX, Topic: scalable machine learning

Christopher Simpkins, Charles L. Isbell, and Nicholas Marquez. Deriving behavior from personality: A reinforcement learning approach. In Proceedings of the Tenth International Conference on Cognitive Modeling (ICCM), 2010.
      Abstract, PDF, BibTeX, Topic: partial programming

Peng Zang, Runhe Tian, Charles L. Isbell, and Andrea Thomaz. Batch versus interactive learning by demonstration. In Proceedings of the Ninth International Conference on Development and Learning (ICDL), 2010.
      Abstract, PDF, BibTeX, Topics: reinforcement learning; human teaching

Peng Zang, Arya Irani, Peng Zhou, Charles L. Isbell, and Andrea Thomaz. Using Training Regimens to Teach Expanding Function Approximators. In Proceedings of the Ninth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2010.
      Abstract, PDF, BibTeX, Topics: reinforcement learning; human teaching

Charles L. Isbell, Lynn Stein, Robb Cutler, Jeffrey Forbes, Linda Fraser, John Impagliazzo, Viera Prolux, Steve Russ, Richard Thomas, and Yan Xu. (Re)Defining Computing Curricula by (Re)Defining Computing. ACM SIGCSE Bulletin, 41(4):195-207, 2009.
      Abstract, BibTeX, Topics: education; curriculum

Olufisayo Omojokun, Charles L. Isbell, and Prasun Dewan. Towards Automatic Personalization of Device Controls. IEEE Transactions on Consumer Electronics, 55(1):269-276, 2009.
      BibTeX, Topics: activity discovery; HCI; adaptive interfaces

Raffay Hamid, Siddhartha Maddi, Amos Johnson, Aaron Bobick, Irfan Essa, and Charles L. Isbell. A Novel Sequence Representation for Unsupervised Analysis of Human Activities. Artificial Intelligence, 173(14), 2009.
      Abstract, PDF, BibTeX, Topics: activity discovery; vision

Liam Mac Dermed and Charles L. Isbell. Solving Stochastic Games. In Advances in Neural Information Processing Systems (NIPS) 22, 2009.
      Abstract, PDF, BibTeX, Topics: reinforcement learning; multi-agent reinforcement learning; game theory

David L. Roberts, Charles L. Isbell, and Mark Riedl. Beyond Adversarial: The Case of Game AI as Storytelling. In Digital Games Research Association (DiGRA) 2009, 2009.
      Abstract, PDF, BibTeX, Topics: entertainment; autonomous agents; drama management

Peng Zang, Peng Zhou, David Minnen, and Charles L. Isbell. Discovering Options from Example Trajectories. In Proceedings of the Twenty-sixth International Conference on Machine Learning (ICML), 2009.
      Abstract, PDF, BibTeX, Topics: activity discovery; reinforcement learning

David L. Roberts, Merrick L. Furst, Charles L. Isbell, and Brian Dorn. Using Influence and Persuasion to Shape Player Experiences. In 2009 Sandbox: ACM SIGGRAPH Video Game Proceedings (SIGGRAPH Sandbox), 2009.
      Abstract, PDF, BibTeX, Topics: entertainment; autonomous agents; computational influence; drama management

Michael Holmes, Alex Gray, and Charles L. Isbell. QUIC-SVD: Fast SVD Using Cosine Trees. In Advances in Neural Information Processing Systems (NIPS) 21, 2009.
      Abstract, PDF, BibTeX, Topic: scalable machine learning

Olufisayo Omojokun, Charles L. Isbell, and Prasun Dewan. Towards Automatic Personalization of Device Controls. In Proceedings of the Twenty-Seventh International Conference on Consumer Electronics (ICCE), 2009.
      BibTeX, Topics: activity discovery; HCI; adaptive interfaces

David L. Roberts and Charles L. Isbell. A Survey and Qualitative Analysis of Recent Advances in Drama Management. International Transactions on Systems Science and Applications, 4(2):61-75, 2008.
      Abstract, PDF, BibTeX, Topics: entertainment; autonomous agents; drama management

David L. Roberts, Charles L. Isbell, and Michael L. Littman. Optimization Problems Involving Collections of Dependent Objects. Annals of Operations Research, 163(1):255-270, 2008.
      Abstract, BibTeX, Topic: optimization

Olufisayo Omojokun, Michael Genovese, and Charles L. Isbell. Partial Signal Extraction for Mobile Media Players. In Proceedings of the Sixth International Conference on Advances in Mobile Computing and Multimedia (MoMM), 2008.
      Abstract, BibTeX, Topics: activity discovery; adaptive interfaces; signal extraction

David L. Roberts, Charles L. Isbell, Mark Riedl, Ian Bogost, and Merrick Furst. On the Use of Computational Models of Influence for Interactive Virtual Experience Management. In Proceedings of the First International Conference on Interactive Digital Storytelling (ICIDS), 2008.
      Abstract, PDF, BibTeX, Topics: entertainment; autonomous agents; computational influence; drama management

Olufisayo Omojokun, Mike Genovese, and Charles L. Isbell. Impact of User Context on Song Selection. In Proceedings of the Sixteenth ACM SIGMM International Conference on Multimedia (ACMMM), 2008.
      Abstract, BibTeX, Topics: activity discovery; HCI; adaptive interfaces

Christopher Simpkins, Sooraj Bhat, Charles L. Isbell, and Michael Mateas. Adaptive Programming: Integrating Reinforcement Learning into a Programming Language. In Proceedings of the Twenty-Third ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA), 2008.
      Abstract, PDF, BibTeX, Topics: partial programming; a2bl

Rudolph Mappus, David Minnen, and Charles L. Isbell. Dimensionality Reduction for Improved Source Separation in fMRI Data. In Proceedings of theInternational Conference on Bio-inspired Systems and Signal Processing (BIOSIGNALS), 2008.
      Abstract, BibTeX, Topics: brain imaging; independent components analysis

Michael Holmes, Alex Gray, and Charles L. Isbell. Ultrafast Monte Carlo for Kernel Estimators and Generalized Statistical Summations. In Advances in Neural Information Processing Systems (NIPS) 20, 2008.
      Abstract, PDF, BibTeX, Topics: optimization; scalable machine learning

David Minnen, Thad Starner, Charles L. Isbell, and Irfan Essa. Detecting Subdimensional Motifs: An Efficient Algorithm for Generalized Multivariate Pattern Discovery. In Proceedings of the Seventh IEEE International Conference on Data Mining (ICDM), 2007.
      Abstract, PDF, BibTeX, Topic: activity discovery

Michael Holmes, Alex Gray, and Charles L. Isbell. Fast Nonparametric Conditional Density Estimation. In Proceedings of the Twenty-Third Conference on Uncertainty in Artificial Intelligence (UAI), 2007.
      Abstract, PDF, BibTeX, Topics: optimization; density estimation; scalable machine learning

David L. Roberts, Sooraj Bhat, Kenneth St. Clair, and Charles L. Isbell. Authorial Idioms for Target Distributions in TTD-MDPs. In Proceedings of the Twenty-Second National Conference on Artificial Intelligence (AAAI), 2007.
      Abstract, PDF, BibTeX, Topics: autonomous agents; drama management; ttd-mdps

David Minnen, Charles L. Isbell, Irfan Essa, and Thad Starner. Discovering Multivariate Motifs using Subsequence Density Estimation. In Proceedings of the Twenty-Second National Conference on Artificial Intelligence (AAAI), 2007.
      Abstract, PDF, BibTeX, Topic: activity discovery

David L. Roberts, Andrew Cantino, and Charles L. Isbell. Player Autonomy versus Designer Intent: A Case Study of Interactive Tour Guides. In Proceedings of the Third Artificial Intelligence and Interactive Digital Entertainment (AIIDE), 2007. We recommend the technical report available under our link for the AAMAS 2007 paper that incorporates parts of this paper.
      BibTeX, Topics: entertainment; autonomous agents; drama management; ttd-mdps

Sooraj Bhat, David L. Roberts, Mark Nelson, Charles L. Isbell, and Michael Mateas. A Globally Optimal Online Algorithm for TTD-MDPs. In Proceedings of the Sixth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2007.
      Abstract, PDF, BibTeX, Topics: entertainment; drama management; ttd-mdps

David L. Roberts, Andrew Cantino, and Charles L. Isbell. Improving Quality of Experience Using TTD-MDP-Based Tour Guides. In Proceedings of the Sixth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2007. The pdf points to a longer technical report.
      Abstract, PDF, BibTeX, Topics: entertainment; autonomous agents; drama management; ttd-mdps

Merrick Furst, Charles L. Isbell, and Mark Guzdial. Threads: How to Restructure a Computer Science Curriculum for a Flat World. In Proceedings of the Thirty-Eighth ACM Technical Symposium on Computer Science Education (SIGCSE), 2007.
      Abstract, PDF, more info, BibTeX, Topics: education; curriculum; threads

Peng Zang and Charles L. Isbell. Managing Domain Knowledge and Multiple Models with Boosting. In Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI), 2007. This version contains some minor corrections from the camera-ready IJCAI paper.
      Abstract, PDF, BibTeX, Topic: boosting

David Minnen, Thad Starner, Irfan Essa, and Charles L. Isbell. Improving Activity Discovery with Automatic Neighborhood Estimation. In Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI), 2007.
      Abstract, PDF, BibTeX, Topic: activity discovery

Manu Sharma, Michael Holmes, Juan Santamaria, Arya Irani, Charles L. Isbell, and Ashwin Ram. Transfer Learning in Real-Time Strategy Games Using Hybrid CBR/RL. In Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI), 2007.
      Abstract, BibTeX, Topics: transfer learning; reinforcement learning

Charles L. Isbell, Michael Kearns, Satinder Singh, Christian R. Shelton, Peter Stone, and Dave Kormann. Cobot in LambdaMOO: An Adaptive Social Statistics Agent. Journal of Autonomous Agents and Multi-Agent Systems, 13(3):327-354, 2006.
      Abstract, PDF, more info, BibTeX, Topics: autonomous agents; cobot; reinforcement learning

Mark J. Nelson, Michael Mateas, David L. Roberts, and Charles L. Isbell. Declarative Optimization-Based Drama Management in Interactive Fiction. IEEE Computer Graphics & Applications, 26(3):32-41, 2006.
      Abstract, PDF, BibTeX, Topics: entertainment; drama management

Tucker Balch, Frank Dellaert, Adam Feldman, Andrew Guillory, Charles L. Isbell, Zia Kahn, Andrew Stein, and Hank Wilde. How AI and Multi-Robot Systems Research Will Accelerate Our Understanding of Social Animal Behavior. Proceedings of the IEEE, 94(7):1445-1463, 2006.
      Abstract, PDF, BibTeX, Topic: modeling

Olufisayo Omojokun, Jeffrey Pierce, Charles L. Isbell, and Prasun Dewan. Comparing End-User and Intelligent Remote Control Interface Generation. Personal and Ubiquitous Computing, 10(2-3):136-143, 2006.
      Abstract, BibTeX, Topics: activity discovery; HCI; adaptive interfaces

David Minnen, Thad Starner, Irfan Essa, and Charles L. Isbell. Discovering Characteristic Actions from On-Body Sensor Data. In Proceedings of the Tenth IEEE International Symposium on Wearable Computers (ISWC), 2006. Nominated for a Best Paper Award.
      Abstract, PDF, BibTeX, Topic: activity discovery

Sooraj Bhat, Charles L. Isbell, and Michael Mateas. On the Difficulty of Modular Reinforcement Learning for Real-World Partial Programming. In Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI), 2006.
      Abstract, PDF, BibTeX, Topics: partial programming; a2bl

David L. Roberts, Mark Nelson, Charles L. Isbell, Michael Mateas, and Michael L. Littman. Targeting Specific Distributions of Trajectories in MDPs. In Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI), 2006.
      Abstract, PDF, BibTeX, Topics: entertainment; drama management; ttd-mdps

Michael Holmes and Charles L. Isbell. Looping Suffix Tree-Based Inference of Partially Observable Hidden State. In Proceedings of the Twenty-Third International Conference on Machine Learning (ICML), 2006. Winner of Distinguished Student Paper Award.
      Abstract, PDF, BibTeX, Topics: state discovery; predictive state representations

Mark Nelson, David L. Roberts, Charles L. Isbell, and Michael Mateas. Reinforcement Learning in Declarative Optimization-Based Drama Management. In Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2006.
      Abstract, PDF, BibTeX, Topics: entertainment; drama management; reinforcement learning

Andrew Guillory, Tucker Balch, and Charles L. Isbell. Learning Executable Models of Behavior from Observations and Low Level Knowledge. In Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2006.
      Abstract, PDF, BibTeX, Topic: modeling

David L. Roberts, Sooraj Bhat, Charles L. Isbell, Brian Cooper, and Jeffrey Pierce. A Decision-Theoretic Approach to File Consistency in Constrained Peer-to-Peer Device Networks. In Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2006. The pdf points to a longer technical report.
      Abstract, PDF, BibTeX, Topics: unison; adaptive networks

Raffay Hamid, S. Maddi, Amos Johnson, S. Batta, Aaron Bobick, Irfan Essa, and Charles L. Isbell. Unsupervised Activity Discovery and Characterization from Event-Streams. In Proceedings of the Twenty-First Conference on Uncertainty in Artificial Intelligence (UAI), 2005. A version of this work was also presented at The Learning Workshop at Snowbird, 2005.
      Abstract, PDF, BibTeX, Topic: activity discovery

Raffay Hamid, Amos Johnson, S. Batta, Aaron Bobick, Charles L. Isbell, and G. Coleman. Detection and Explanation of Anomalous Activities: Representing Activities as Bags of Event n-Grams. In Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 1031-1038, 2005.
      Abstract, PDF, BibTeX, Topics: activity discovery; anomaly detection

Michael Holmes and Charles L. Isbell. Schema Learning: Experience-based Construction of Predictive Action Models. In Advances in Neural Information Processing Systems (NIPS) 17, pages 585-562, 2005.
      Abstract, PDF, BibTeX, Topics: state discovery; schemas; predictive state representations

Charles L. Isbell and Jeff Pierce. An IP Continuum for Adaptive Interface Design. In Proceedings of the 11th International Conference on Human-Computer Interaction (HCII), 2005.
      Abstract, PDF, BibTeX, Topics: HCI; adaptive interfaces; IP Continuum

Charles L. Isbell, Olufisayo Omojokun, and Jeffrey Pierce. From Devices to Tasks: Automatic Task Prediction for Personalized Appliance Control. Personal and Ubiquitous Computing, 8(3):146-153, 2004.
      Abstract, PDF, BibTeX, Topics: activity discovery; HCI; adaptive interfaces

Brian Landry, Jeffrey Pierce, and Charles L. Isbell. Supporting Routine Decision-Making with a Next-Generation Alarm Clock. Personal and Ubiquitous Computing, 8(3):154-160, 2004.
      Abstract, BibTeX, Topic: HCI

Yukio Ohsawa, Peter McBurney, Simon Parsons, Christopher A. Miller, Alan Schultz, Jean Scholtz, Michael A. Goodrich, Eugene Santos Jr, Benjamin Bell, Charles L. Isbell, and Michael L. Littman. AAAI-2002 Fall Symposium Series. AI Magazine, 24(1):95-98, 2003.
      BibTeX

Lawrence Saul, Daniel Lee, Charles L. Isbell, and Yaun LeCun. Real time voice processing with audiovisual feedback: toward autonomous agents with perfect pitch. In Advances in Neural Information Processing Systems (NIPS) 15, pages 1205-1212, 2003.
      Abstract, PDF, BibTeX, Topic: autonomous agents

Michael Kearns, Charles L. Isbell, Satinder Singh, Diane Litman, and Jessica Howe. CobotDS: A Spoken Dialogue System for Chat. In Proceedings of the Nineteenth National Conference on Artificial Intelligence (AAAI), pages 435-440, 2002. A version of this work was also presented at The Learning Workshop at Snowbird, 2001.
      Abstract, PDF, more info, BibTeX, Topics: autonomous agents; cobot

Charles L. Isbell, Christian Shelton, Michael Kearns, Satinder Singh, and Peter Stone. A Social Reinforcement Learning Agent. In Proceedings of the Fifth International Conference on Autonomous Agents, pages 377-384, 2001. Winner of Best Paper Award. A version of this paper was also presented at NIPS 14.
      Abstract, PDF, more info, BibTeX, Topics: autonomous agents; cobot; reinforcement learning

Charles L. Isbell, Michael Kearns, Dave Kormann, Satinder Singh, and Peter Stone. Cobot in LambdaMOO: A Social Statistics Agent. In Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI), pages 36-41, 2000. A version of this paper was also presented at WIRE 2000.
      Abstract, PDF, more info, BibTeX, Topics: autonomous agents; cobot

Charles L. Isbell and Parry Husbands. The Parallel Problems Server: An Interactive Tool for Large-Scale Machine Learning. In Advances in Neural Information Processing Systems (NIPS) 12, pages 703-709, 2000.
      Abstract, PDF, BibTeX, Topics: text retrieval; scalable machine learning; ppserver

Parry Husbands and Charles L. Isbell. MITMatlab: A Tool for Interactive Supercomputing. In Proceedings of the Ninth SIAM Conference on Parallel Processing for Scientific Computing., 1999.
      BibTeX, Topics: scalable machine learning; ppserver

Charles L. Isbell and Paul Viola. Restructuring Sparse High Dimensional Data for Effective Information Retrieval. In Advances in Neural Information Processing Systems (NIPS) 11, pages 480-486, 1999.
      Abstract, PDF, BibTeX, Topics: text retrieval; independent components analysis; scalable machine learning; ppserver

Charles L. Isbell. Sparse Multi-Level Representations for Text Retrieval. PhD thesis, Massachusetts Institute of Technology, Cambridge, MA, 1998.
      BibTeX, Topics: independent components analysis; text retrieval; scalable machine learning; ppserver

Parry Husbands and Charles L. Isbell. Interactive Supercomputing with MITMatlab. In The Second IMA Conference on Parallel Computation, 1998.
      PDF, BibTeX, Topic: ppserver

Deborah McGuiness, Charles L. Isbell, M. Parker, Peter Patel-Schneider, Lori Resnick, and Chris Welty. A Description Logic-Based Configurator for the Web. In Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI), 1998.
      BibTeX, Topics: CLASSIC; knowledge representation

Parry Husbands and Charles L. Isbell. The Parallel Problems Server: A Client-Server Model for Large Scale Scientific Computation. In Proceedings of the Third International Conference on Vector and Parallel Processing (VECPAR), pages 156-169, 1998.
      Abstract, PDF, BibTeX, Topic: ppserver

Jeremy De Bonet, Charles L. Isbell, and Paul Viola. MIMIC: Finding Optima by Estimating Probability Densities. In Advances in Neural Information Processing Systems (NIPS) 9, pages 424-430, 1997. A longer version that includes a derivation for MIMIC with trees can be found here
      Abstract, PDF, BibTeX, Topic: randomized optimization

Deborah McGuiness, Lori Resnick, and Charles L. Isbell. Description Logic in Practice: A CLASSIC Application. In Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence (IJCAI), 1995.
      BibTeX, Topics: CLASSIC; knowledge representation

Charles L. Isbell. Explorations of the Practical Issues of Using Temporal Difference Learning Methods for Prediction-Control Tasks. Master's thesis, Massachusetts Institute of Technology, Cambridge, MA, 1992.
      BibTeX, Topic: reinforcement learning


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