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Here's a partial list of my publications, including workshop papers and such. 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.
Charles L. Isbell, Michael Littman, and Peter Norvig.
Software Engineering of Machine Learning Systems.
Communications of the ACM, 66(2), February 2023.
→ BibTeX, Topics: machine learning; software engineering; education
Shray Bansal, Jin Xu, Ayanna Howard, and Charles L. Isbell.
Bayes-Nash: Bayesian Inference for Nash Equilibrium Selection in
Human-Robot Parallel Play.
Autonomous Robots, 46(1):217–230, 2022.
→ Abstract, BibTeX, Topics: interactive machine learning; game theory
Shray Bansal, Miguel Morales, Jin Xu, Ayanna Howard, and Charles L. Isbell.
Nash Equilibria in Bayesian Games for Coordinating with Imperfect
Humans.
In Workshop on Strategic multi-agent interactions: game theory
for robot learning and decision making at CoRL, 2022.
→ BibTeX, Topics: game theory; multiagent learning; parallel play
David A. Joyner and Charles L. Isbell.
The Distributed Classroom.
MIT Press, Cambridge, 2021.
→ BibTeX, Topic: education
Shray Bansal, Jin Xu, Ayanna Howard, and Charles L. Isbell.
Bayesian Inference for Human-Robot Coordination in Parallel Play.
In Workshop on Cooperative AI at NeurIPS, 2021.
→ BibTeX, Topics: game theory; multiagent learning; parallel play
Shray Bansal, Rhys Newbury, Wesley Chan, Akansel Cosgun, Aimee Allen, Dana
Kulić, Tom Drummond, and Charles L. Isbell.
Supportive Actions for Manipulation in Human-Robot Coworker Teams.
In Proceedings of the the 2020 IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS), 2020.
→ BibTeX, Topics: interactive machine learning; robotics
Ashley Edwards, Himanshu Sahni, Rosanne Liu, Jane Hung, Ankit Jain, Rui Wang,
Adrien Ecoffet, Thomas Miconi, Charles L. Isbell, and Jason Yosinski.
Estimating Q(s,s') with Deep Deterministic Dynamics Gradients.
In Proceedings of the 37th International Conference on Machine
Learning (ICML), 2020.
→ BibTeX, Topic: reinforcement learning
Shray Bansal, Jin Xu, Ayanna Howard, and Charles L. Isbell.
A Bayesian Framework for Nash Equilibrium Inference in Human-Robot
Parallel Play.
In Proceedings of the 2020 Conference on Robotics: Science and
Systems (RSS), 2020.
→ Abstract, PDF, BibTeX, Topics: interactive machine learning; robotics
Himanshu Sahni, Shray Bansal, and Charles L. Isbell.
Attention Driven Dynamic Memory Maps.
In Workshop on Bridging AI and Cognitive Science at ICLR, 2020.
→ BibTeX, Topic: attention
Ashley Edwards, Himanshu Sahni, Yannick Schroecker, and Charles L. Isbell.
Imitating Latent Policies from Observation.
In Proceedings of the 36th International Conference on Machine
Learning (ICML), 2019.
→ BibTeX, Topics: interactive machine learning; reinforcement learning
David Joyner and Charles L. Isbell.
Master's at Scale: Five Years in a Scalable Online Graduate Degree.
In The Sixth ACM Conference on Learning @ Scale, 2019.
→ BibTeX, Topic: education
David Joyner, Charles L. Isbell, Thad Starner, and Ashok Goel.
Five Years of Graduate CS Education Online and at Scale.
In Proceedings of the 2019 ACM Global Computing Education
Conference (CompEd), 2019.
→ Abstract, BibTeX, Topic: education
Christopher Simpkins and Charles L. Isbell.
Composable Modular Reinforcement Learning.
In Proceedings of the Thirty-Third National Conference on
Artificial Intelligence (AAAI), 2019.
→ Abstract, PDF, BibTeX, Topics: reinforcement learning; partial programming
Shray Bansal, Mustafa Mukadam, and Charles L. Isbell.
Interaction-Aware Planning via Nash Equilibria for Manipulation in a
Shared Workspace.
In Workshop on Human Movement Science for Physical Human-Robot
Collaboration at ICRA, 2019.
→ BibTeX, Topics: game theory; multiagent learning; parallel play
Ashley Edwards and Charles L. Isbell.
Perceptual Values from Observation.
In Workshop on Self-Supervised Learning at ICML, 2019.
→ BibTeX, Topic: perception
Rahul Sawhney, Fuxin Li, Henrik Christensen, and Charles L. Isbell.
Purely Geometric Scene Association and Retrieval: A case for
macro-scale 3D geometry.
In Proceedings of the the 2018 IEEE International Conference on
Robotics and Automation (ICRA), 2018.
→ Abstract, PDF, BibTeX, Topic: geometry
Douglas H. Fisher, Charles L. Isbell, Michael L. Littman, Michael Wollowski,
Todd Neller, and James Boerkoel.
Ask Me Anything About MOOCs.
AI Magazine, 38(2):7–12, 2017.
→ BibTeX, Topic: education
Yannick Schroecker and Charles L. Isbell.
State Aware Imitation Learning.
In Advances in Neural Information Processing Systems (NIPS) 31,
2017.
→ Abstract, PDF, BibTeX, Topics: interactive machine learning; reinforcement learning
Yannick Schroecker and Charles L. Isbell.
SAIL: A Temporal Difference Approach to State Aware Imitation
Learning.
In The 3rd Multidisciplinary Conference on Reinforcement
Learning and Decision Making (RLDM), 2017. A longer version of this paper is available in NIPS 2017.
→ BibTeX, Topic: reinforcement learning
Ashley Edwards, Srijan Sood, and Charles L. Isbell.
Cross-Domain Perceptual Rewards for Reinforcement Learning.
In The 3rd Multidisciplinary Conference on Reinforcement
Learning and Decision Making (RLDM), 2017.
→ BibTeX, Topic: reinforcement learning
Saurabh Kumar, Himanshu Sahni, Farhan Tejani, Yannick Schroecker, and
Charles L. Isbell.
State Space Decomposition and Subgoal Creation for Transfer in Deep
Reinforcement Learning.
In The 3rd Multidisciplinary Conference on Reinforcement
Learning and Decision Making (RLDM), 2017.
→ BibTeX, Topic: reinforcement learning
Hamid Reza Hassanzadeh, Pushkar Kolhe, Charles L. Isbell, and May D. Wang.
MotifMark: Finding Regulatory Motifs in DNA Sequences.
In 39th Annual International Conference of the IEEE Engineering
in Medicine and Biology Society (EMBC) 31, 2017.
→ Abstract, PDF, BibTeX, Topics: motifs; bioinformatics
Sam Krening, Brent Harrison, Karen Feigh, Charles L. Isbell, Mark Riedl, and
Andrea Thomaz.
Learning from Explanations Using Sentiment and Advice in RL.
IEEE Transactions on Cognitive and Developmental Systems,
9(1):44–55, 2016.
→ Abstract, BibTeX, Topics: interactive machine learning; reinforcement learning; human teaching
Jonathan Scholz, Jindal Nehchal, Martin Levihn, and Charles L. Isbell.
Navigation Among Movable Obstacles with Learned Dynamic
Constraints.
In Proceedings of the the 2016 IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS), 2016.
→ Abstract, PDF, BibTeX, Topics: reinforcement learning; robotics
Kaushik Subramanian, Charles L. Isbell, and Andrea Thomaz.
Exploration from Demonstration for Interactive Reinforcement
Learning.
In Proceedings of the 15th International Joint Conference on
Autonomous Agents and Multiagent Systems (AAMAS), 2016.
→ Abstract, PDF, BibTeX, Topics: interactive machine learning; reinforcement learning; human teaching
Samantha Krening, Brent Harrison, Karen Feigh, Charles L. Isbell, and Andrea
Thomaz.
Object-Focused Advice in Reinforcement Learning.
In Proceedings of the 15th International Joint Conference on
Autonomous Agents and Multiagent Systems (AAMAS), 2016.
→ BibTeX, Topics: interactive machine learning; reinforcement learning; human teaching
Himanshu Sahni, Brent Harrison, Kaushik Subramanian, Thomas Cederborg,
Charles L. Isbell, and Andrea Thomaz.
Policy Shaping in Domains with Multiple Optimal Policies.
In Proceedings of the 15th International Joint Conference on
Autonomous Agents and Multiagent Systems (AAMAS), 2016.
→ BibTeX, Topics: interactive machine learning; reinforcement learning; human teaching; policy shaping
David Joyner, Ashok Goel, and Charles L. Isbell.
The Unexpected Pedagogical Benefits of Making Higher Education
Accessible.
In The Third ACM Conference on Learning @ Scale, 2016.
→ PDF, BibTeX, Topic: education
Pushkar Kolhe, Michael Littman, and Charles L. Isbell.
Peer Reviewing Short Answers using Comparative Judgement.
In The Third ACM Conference on Learning @ Scale, 2016.
→ Abstract, PDF, BibTeX, Topic: education
Eric Eaton, Tom Dietterich, Maria Gini, Barbara J. Grosz, Charles L. Isbell,
Subbarao Kambhampati, Michael Littman, Francesca Rossi, Stuart Russell, Peter
Stone, Tony Walsh, and Michael Wooldridge.
Who Speaks for AI?
AI Matters, 2(2):4–14, Dec 2015.
→ BibTeX, Topic: AI
Thomas Cederborg, Ishaan Grover, Charles L. Isbell, and Andrea L Thomaz.
Policy Shaping With Human Teachers.
In Proceedings of the Twenty-Fourth International Joint
Conference on Artificial Intelligence (IJCAI), 2015.
→ Abstract, PDF, BibTeX, Topics: interactive machine learning; reinforcement learning; human teaching; policy shaping
Jesse Rosalia, Guliz Tokadli, Charles L. Isbell, Andrea Thomaz, and Karen
Feigh.
Discovery, Evaluation, and Exploration of Human Supplied Options and
Constraints.
In Proceedings of the 14th International Joint Conference on
Autonomous Agents and Multiagent Systems (AAMAS), 2015.
→ Abstract, PDF, BibTeX, Topics: interactive machine learning; reinforcement learning; human teaching; constraints
Jonathan Scholz, Martin Levihn, Charles L. Isbell, Henrik Christensen, and Mike
Stilman.
Learning Non-Holonomic Object Models for Mobile Manipulation.
In Proceedings of the the 2015 IEEE International Conference on
Robotics and Automation (ICRA), 2015.
→ Abstract, PDF, BibTeX, Topics: reinforcement learning; robotics
Ashley Edwards, Charles L. Isbell, and Michael Littman.
Expressing Tasks Robustly via Multiple Discount Factors.
In The 2nd Multidisciplinary Conference on Reinforcement
Learning and Decision Making (RLDM), 2015.
→ BibTeX, Topic: reinforcement learning
Luis Carlos Cobo Rus, Kaushik Subramanian, Charles L. Isbell, Aaron Lanterman,
and Andrea Thomaz.
Abstraction from Demonstration for Efficient Reinforcement Learning
in High-Dimensional Domains.
Artificial Intelligence, 216(0):103–128, 2014.
→ Abstract, BibTeX, Topics: interactive machine learning; reinforcement learning; human teaching
David Roberts and Charles L. Isbell.
Lessons on Using Computationally Generated Influence for Shaping
Narrative Experiences.
Transactions on Computational Intelligence and AI in Games,
6(2):1–15, 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.
→ Abstract, PDF, BibTeX, Topics: reinforcement learning; robotics
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.
→ Abstract, PDF, 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.
→ Abstract, PDF, 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
Jonathan Scholz, Martin Levihn, and Charles L. Isbell.
What Does Physics Bias: A Comparison of Model Priors for Robot
Manipulation.
In The 1st Multidisciplinary Conference on Reinforcement
Learning and Decision Making (RLDM), 2013.
→ BibTeX, Topic: reinforcement learning
Shane Griffith, Kaushik Subramanian, Jonathan Scholz, Charles L. Isbell, and
Andrea Thomaz.
Policy Shaping: Integrating Human Feedback with Reinforcement
Learning.
In The 1st Multidisciplinary Conference on Reinforcement
Learning and Decision Making (RLDM), 2013.
→ BibTeX, Topics: interactive machine learning; reinforcement learning; human teaching; policy shaping
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
Kaushik Subramanian, Charles L. Isbell, and Andrea Thomaz.
Learning Options through Human Interaction.
In Workshop on Agents Learning Interactively from Human Teachers
at IJCAI, 2011.
→ 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, PDF, 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
Peng Zang, Charles L. Isbell, and Andrea Thomaz.
Exploiting Training Regimens to Improve Learning.
In Multidisciplinary Symposium on Reinforcement Learning at
ICML, 2009.
→ PDF, BibTeX, Topics: reinforcement learning; hmi
David L. Roberts, Harikrishna Narayanan, and Charles L. Isbell.
Learning to influence emotional responses for interactive
storytelling.
In Proceedings of the AAAI 2009 Spring Symposium on Intelligent
Narrative Technologies II, 2009.
→ Abstract, PDF, BibTeX, Topic: drama management
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
Andrew Cantino, Charles L. Isbell, and Gregory Turk.
Minima Filling for Simulation of Muscular Hydrostat Motion.
Technical Report GIT-GVU-08-01, Georgia Institute of Technology,
2008.
→ Abstract, PDF, BibTeX, Topic: optimization
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, more info, PDF, 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
Peng Zang, Arya Irani, and Charles L. Isbell.
Horizon-Based Value Iteration.
Technical Report GIT-IC-07-07, Georgia Institute of Technology, 2007.
→ Abstract, PDF, BibTeX, Topic: reinforcement learning
David Roberts, Mark Riedl, and Charles L. Isbell.
Opportunities for Machine Learning to Impact Interactive Narrative.
In Workshop on Machine Learning and Games at NIPS, 2007.
→ BibTeX, Topic: drama management
Michael Holmes, Alexander Gray, and Charles L. Isbell.
Fast SVD for Large-Scale Matrices.
In Workshop on Efficient Machine Learning at NIPS, 2007.
→ BibTeX, Topic: scalable machine learning
David Minnen, Peng Zang, Charles L. Isbell, and Thad Starner.
Boosting Diverse Learners for Domain Agnostic Time Series
Classification.
In Workshop and Challenge on Time Series Classification at
SIGKDD, 2007.
→ BibTeX, Topics: boosting; activity discovery
David Roberts, Christina Strong, and Charles L. Isbell.
Using Feature Value Distributions to Estimate Player Satisfaction
Through an Author's Eyes.
In AAAI 2007 Fall Symposium on Intelligent Narrative
Technologies, 2007.
→ BibTeX, Topics: entertainment; drama management
Peng Zang and Charles L. Isbell.
Similarity in Reinforcement Learning.
In Workshop on Knowledge Discovery and Similarity in Case-Based
Reasoning at ICCBR, 2007.
→ BibTeX, Topics: case based reasoning; reinforcement learning
David Minnen, Thad Starner, Irfan Essa, and Charles L. Isbell.
Pattern Discovery for Locating Motifs in Multivariate, Real-valued
Time-series Data.
In The Learning Workshop (SNOWBIRD), 2007.
→ BibTeX, Topic: activity discovery
Michael Holmes, Alex Gray, and Charles L. Isbell.
Fast Nonparametric Conditional Density Estimation.
In The Learning Workshop (SNOWBIRD), 2007.
→ BibTeX, Topics: optimization; density estimation; scalable machine learning
David Roberts and Charles L. Isbell.
Desiderata for Managers of Interactive Experiences: A Survey of
Recent Advances in Drama Management.
In The Agent Based Systems for Human Learning and Entertainment
Workshop (ABSHLE) at AAMAS, 2007.
→ BibTeX, Topic: drama management
David Roberts, Christina Strong, and Charles L. Isbell.
Estimating Player Satisfaction Through the Author's Eyes.
In Workshop on Optimizing Player Satisfaction at AIIDE, 2007.
→ BibTeX, Topics: entertainment; drama management
Andrew Cantino, David Roberts, and Charles L. Isbell.
Autonomous Nondeterministic Tour Guides: Improving Quality of
Experience with TTD-MDPs.
Technical Report GIT-IIC-07-02, Georgia Institute of Technology,
2007.
→ BibTeX, Topic: drama management
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, more info, PDF, 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
Kevin Quennesson, Elias Ioup, and Charles L. Isbell.
Wavelet statistics for human motion classification.
In National Conference on Artificial Intelligence (AAAI) Special
Track, 2006.
→ BibTeX, Topic: classification
David Minnen, Thad Starner, Irfan Essa, and Charles L. Isbell.
Activity Discovery: Sparse Motifs from Multivariate Time Series.
In The Learning Workshop (SNOWBIRD), 2006.
→ BibTeX, Topic: activity discovery
Michael Holmes and Charles L. Isbell.
Looping Suffix Trees for Inference of Partially Observable Hidden
State.
In The Learning Workshop (SNOWBIRD), 2006.
→ BibTeX, Topics: state discovery; predictive state representations
David Roberts, Sooraj Bhat, Charles L. Isbell, Brian F. Cooper, and Jeffrey S.
Pierce.
A Decision Theoretic Approach to File Consistency in Constrained
Peer-to-Peer Device Networks.
Technical Report GIT-CC-06-05, College of Computing, Georgia
Institute of Technology, 2006.
→ Abstract, PDF, BibTeX, Topic: accord
Brian F. Cooper, Charles L. Isbell, Jeffrey S. Pierce, David L. Roberts, and
Sooraj Bhat.
Accord: Middleware support for contextual ubiquitous data management
on user devices.
Technical Report GIT-CC-06-06, College of Computing, Georgia
Institute of Technology, 2006.
→ Abstract, PDF, BibTeX, Topic: accord
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
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 The Learning Workshop (SNOWBIRD), 2005.
→ BibTeX, Topic: activity discovery
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, Topic: AI
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
Olufisayo Omojokun and Charles L. Isbell.
User Modelling for Personalized Universal Appliance Application
Interaction.
In Proceedings of the Richard Tapia Celebration of Diversity in
Computing Conference, pages 65–68, 2003.
→ BibTeX, Topics: activity discovery; HCI; adaptive interfaces
Olufisayo Omojokun and Charles L. Isbell.
Supporting Personalized Agents in Universal Appliance Interaction.
In Proceedings of the Forty-First Annual ACM Southeast
Conference, 2003.
→ BibTeX, Topics: activity discovery; HCI; adaptive interfaces
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, more info, PDF, BibTeX, Topics: autonomous agents; cobot
Olufisayo Omojokun, Charles L. Isbell, and Prasun Dewan.
An architecture for Supporting Personalized Agents in Appliance
Interaction.
In AAAI Fall Symposium on Personalized Agents, 2002.
→ BibTeX, Topics: HCI; adaptive interfaces
Charles L. Isbell, Gavin Bell, Brian Amento, Steve Whittaker, and Jonathan
Helfman.
IshMail: Designing Advanced Email Systems.
In Proceedings of the CSCW Workshop on Redesigning Email for the
21st century, 2002.
→ Abstract, BibTeX, Topic: email
Charles L. Isbell, Gavin Bell, Brian Amento, Steve Whittaker, and Jonathan
Helfman.
IshMail.
In Proceedings of the the Fifteenth Annual ACM Symposium on User
Interface Software and Technology (Demo), 2002.
→ BibTeX, Topic: email
Charles L. Isbell, Christian Shelton, Michael Kearns, Satinder Singh, and Peter
Stone.
Cobot: A Social Reinforcement Learning Agent.
In Advances in Neural Information Processing Systems (NIPS) 14,
pages 1393–1400, 2002. A version of this paper was also presented at Agents 2001. The interested reader should read the JAAMAS article.
→ Abstract, more info, BibTeX, Topics: autonomous agents; cobot; reinforcement learning
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, more info, PDF, BibTeX, Topics: autonomous agents; cobot; reinforcement learning
Michael Kearns, Charles L. Isbell, Satinder Singh, Diane Litman, and Jessica
Howe.
CobotDS: A Spoken Dialogue System for Chat.
In The Learning Workshop (SNOWBIRD), 2001.
→ BibTeX, Topics: dialogue systems; 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, more info, PDF, 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
Charles L. Isbell, Michael Kearns, Dave Kormann, Satinder Singh, and Peter
Stone.
Cobot in LambdaMOO: A Social Statistics Agent.
In Proceedings of the Workshop on Interactive Robotics and
Entertainment (WIRE), 2000.
→ BibTeX, Topics: autonomous agents; cobot; reinforcement learning
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
Parry Husbands and Charles L. Isbell.
The Parallel Problems Server.
In Proceedings of the 1998 MIT Workshop on High Performance
Computing in Science and Engineering, 1998.
→ 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
Alex Borgida, Charles L. Isbell, and Deborah McGuiness.
Reasoning with Black Boxes: Handling Test Concepts in CLASSIC.
In Proceedings of the Workshop on Description Logics, 1996.
→ BibTeX, Topics: CLASSIC; knowledge representation
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
Jonathan Helfman and Charles L. Isbell.
Ishmail: Immediate Information.
Technical report, AT&T Labs, 1995.
→ BibTeX, Topic: email
Jonathan Helfman and Charles L. Isbell.
Ishmail User's Guide.
Technical report, AT&T Labs, 1995.
→ BibTeX, Topic: email
Jonathan Helfman and Charles L. Isbell.
A Programmer's Guide to Ishmail.
Technical report, AT&T Labs, 1995.
→ BibTeX, Topic: email
Lori Resnick, Alex Borgida, Ronald J. Brachman, Deborah McGuiness, Peter Patel
Schneider, Charles L. Isbell, and Kevin Zalondek.
CLASSIC Description and Reference Manual for the Common Lisp
Implementation: Version 2.3.
Technical report, AT&T Labs, 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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