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ORCIDCharles L. Isbell Jr.
Charles Lee Isbell Jr. – Charles Isbell
Person information
- affiliation: Georgia Institute of Technology, College of Computing, Atlanta, GA, USA
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2020 – today
- 2023
[j22]Charles Isbell, Michael L. Littman, Peter Norvig:
Software Engineering of Machine Learning Systems. Commun. ACM 66(2): 35-37 (2023)- 2022
- [j21]Shray Bansal
, Jin Xu, Ayanna M. Howard, Charles Isbell:
Bayes-Nash: Bayesian inference for Nash equilibrium selection in human-robot parallel play. Auton. Robots 46(1): 217-230 (2022) - [i19]Michael L. Littman, Ifeoma Ajunwa, Guy Berger, Craig Boutilier, Morgan Currie, Finale Doshi-Velez, Gillian K. Hadfield, Michael C. Horowitz, Charles Isbell, Hiroaki Kitano, Karen Levy, Terah Lyons, Melanie Mitchell, Julie Shah, Steven A. Sloman, Shannon Vallor, Toby Walsh:
Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report. CoRR abs/2210.15767 (2022) - 2021
- [i18]Himanshu Sahni, Charles Isbell:
Hard Attention Control By Mutual Information Maximization. CoRR abs/2103.06371 (2021) - 2020
- [c81]Ashley D. Edwards, Himanshu Sahni, Rosanne Liu, Jane Hung, Ankit Jain, Rui Wang, Adrien Ecoffet, Thomas Miconi, Charles Isbell, Jason Yosinski:
Estimating Q(s,s') with Deep Deterministic Dynamics Gradients. ICML 2020: 2825-2835 - [c80]Shray Bansal, Rhys Newbury, Wesley P. Chan, Akansel Cosgun, Aimee Allen, Dana Kulic, Tom Drummond, Charles Isbell:
Supportive Actions for Manipulation in Human-Robot Coworker Teams. IROS 2020: 11261-11267 - [c79]Shray Bansal, Jin Xu, Ayanna M. Howard, Charles Isbell:
A Bayesian Framework for Nash Equilibrium Inference in Human-Robot Parallel Play. Robotics: Science and Systems 2020 - [i17]Yannick Schroecker, Charles L. Isbell Jr.:
Universal Value Density Estimation for Imitation Learning and Goal-Conditioned Reinforcement Learning. CoRR abs/2002.06473 (2020) - [i16]Ashley D. Edwards, Himanshu Sahni, Rosanne Liu, Jane Hung, Ankit Jain, Rui Wang, Adrien Ecoffet, Thomas Miconi, Charles Isbell, Jason Yosinski:
Estimating Q(s, s') with Deep Deterministic Dynamics Gradients. CoRR abs/2002.09505 (2020) - [i15]Shray Bansal, Rhys Newbury, Wesley P. Chan, Akansel Cosgun, Aimee Allen, Dana Kulic, Tom Drummond, Charles Isbell:
Supportive Actions for Manipulation in Human-Robot Coworker Teams. CoRR abs/2005.00769 (2020) - [i14]Shray Bansal, Jin Xu, Ayanna M. Howard, Charles Isbell:
A Bayesian Framework for Nash Equilibrium Inference in Human-Robot Parallel Play. CoRR abs/2006.05729 (2020)
2010 – 2019
- 2019
- [c78]Christopher L. Simpkins, Charles L. Isbell Jr.:
Composable Modular Reinforcement Learning. AAAI 2019: 4975-4982 - [c77]David A. Joyner, Charles L. Isbell Jr., Thad Starner, Ashok K. Goel:
Five Years of Graduate CS Education Online and at Scale. CompEd 2019: 16-22 - [c76]Ashley D. Edwards, Himanshu Sahni, Yannick Schroecker, Charles L. Isbell Jr.:
Imitating Latent Policies from Observation. ICML 2019: 1755-1763 - [c75]David A. Joyner, Charles L. Isbell Jr.:
Master's at Scale: Five Years in a Scalable Online Graduate Degree. L@S 2019: 21:1-21:10 - [i13]Ashley D. Edwards, Charles L. Isbell Jr.:
Perceptual Values from Observation. CoRR abs/1905.07861 (2019) - 2018
- [c74]Eric Roberts, Tracy Camp, David E. Culler, Charles L. Isbell Jr., Jodi L. Tims:
Rising CS Enrollments: Meeting the Challenges. SIGCSE 2018: 539-540 - [i12]Ashley D. Edwards, Himanshu Sahni, Yannick Schroecker, Charles L. Isbell Jr.:
Imitating Latent Policies from Observation. CoRR abs/1805.07914 (2018) - [i11]Rahul Sawhney, Fuxin Li, Henrik I. Christensen, Charles L. Isbell Jr.:
Purely Geometric Scene Association and Retrieval - A Case for Macro Scale 3D Geometry. CoRR abs/1808.01343 (2018) - 2017
- [j20]Doug Fisher, Charles Lee Isbell Jr., Michael L. Littman, Michael Wollowski, Todd W. Neller, Jim Boerkoel:
Ask Me Anything about MOOCs. AI Mag. 38(2): 7-12 (2017) - [j19]Samantha Krening, Brent Harrison, Karen M. Feigh, Charles Lee Isbell Jr., Mark O. Riedl, Andrea Thomaz:
Learning From Explanations Using Sentiment and Advice in RL. IEEE Trans. Cogn. Dev. Syst. 9(1): 44-55 (2017) - [c73]Hamid Reza Hassanzadeh, Pushkar Kolhe, Charles L. Isbell Jr., May D. Wang:
MotifMark: Finding regulatory motifs in DNA sequences. EMBC 2017: 3890-3893 - [c72]Yannick Schroecker, Charles L. Isbell Jr.:
State Aware Imitation Learning. NIPS 2017: 2911-2920 - [i10]Michael L. Littman, Ufuk Topcu, Jie Fu, Charles Lee Isbell Jr., Min Wen, James MacGlashan:
Environment-Independent Task Specifications via GLTL. CoRR abs/1704.04341 (2017) - [i9]Hamid Reza Hassanzadeh, Pushkar Kolhe, Charles L. Isbell Jr., May D. Wang:
MotifMark: Finding Regulatory Motifs in DNA Sequences. CoRR abs/1705.03321 (2017) - [i8]Himanshu Sahni, Saurabh Kumar, Farhan Tejani, Yannick Schroecker, Charles Lee Isbell Jr.:
State Space Decomposition and Subgoal Creation for Transfer in Deep Reinforcement Learning. CoRR abs/1705.08997 (2017) - [i7]Ashley D. Edwards, Charles Lee Isbell Jr.:
Cross-Domain Perceptual Reward Functions. CoRR abs/1705.09045 (2017) - [i6]Ashley D. Edwards, Charles Lee Isbell Jr.:
Transferring Agent Behaviors from Videos via Motion GANs. CoRR abs/1711.07676 (2017) - [i5]Himanshu Sahni, Saurabh Kumar, Farhan Tejani, Charles L. Isbell Jr.:
Learning to Compose Skills. CoRR abs/1711.11289 (2017) - 2016
- [c71]Kaushik Subramanian, Charles Lee Isbell Jr., Andrea Lockerd Thomaz:
Exploration from Demonstration for Interactive Reinforcement Learning. AAMAS 2016: 447-456 - [c70]Samantha Krening, Brent Harrison, Karen M. Feigh, Charles L. Isbell Jr., Andrea Thomaz:
Object-Focused Advice in Reinforcement Learning. AAMAS 2016: 1447-1448 - [c69]Himanshu Sahni, Brent Harrison, Kaushik Subramanian, Thomas Cederborg, Charles L. Isbell Jr., Andrea Thomaz:
Policy Shaping in Domains with Multiple Optimal Policies: (Extended Abstract). AAMAS 2016: 1455-1456 - [c68]Jonathan Scholz, Nehchal Jindal, Martin Levihn, Charles L. Isbell Jr., Henrik I. Christensen:
Navigation Among Movable Obstacles with learned dynamic constraints. IROS 2016: 3706-3713 - [c67]David A. Joyner, Ashok K. Goel, Charles Lee Isbell Jr.:
The Unexpected Pedagogical Benefits of Making Higher Education Accessible. L@S 2016: 117-120 - [c66]Pushkar Kolhe, Michael L. Littman, Charles L. Isbell Jr.:
Peer Reviewing Short Answers using Comparative Judgement. L@S 2016: 241-244 - [i4]Ashley D. Edwards, Charles Lee Isbell Jr., Atsuo Takanishi:
Perceptual Reward Functions. CoRR abs/1608.03824 (2016) - 2015
- [j18]Eric Eaton, Tom Dietterich, Maria L. Gini, Barbara J. Grosz, Charles L. Isbell Jr., Subbarao Kambhampati, Michael L. Littman, Francesca Rossi, Stuart Russell, Peter Stone, Toby Walsh, Michael J. Wooldridge:
Who speaks for AI? AI Matters 2(2): 4-14 (2015) - [c65]Jesse Rosalia, Güliz Tokadli, Charles Lee Isbell Jr., Karen M. Feigh:
Discovery, Evaluation, and Exploration of Human Supplied Options and Constraints. AAMAS 2015: 1873-1874 - [c64]Jonathan Scholz, Martin Levihn, Charles L. Isbell Jr., Henrik I. Christensen, Mike Stilman:
Learning non-holonomic object models for mobile manipulation. ICRA 2015: 5531-5536 - [c63]Thomas Cederborg, Ishaan Grover, Charles L. Isbell Jr., Andrea Lockerd Thomaz:
Policy Shaping with Human Teachers. IJCAI 2015: 3366-3372 - 2014
- [j17]Luis C. Cobo, Kaushik Subramanian, Charles Lee Isbell Jr., Aaron D. Lanterman, Andrea Lockerd Thomaz:
Abstraction from demonstration for efficient reinforcement learning in high-dimensional domains. Artif. Intell. 216: 103-128 (2014) - [j16]David L. Roberts, Charles L. Isbell Jr.:
Lessons on Using Computationally Generated Influence for Shaping Narrative Experiences. IEEE Trans. Comput. Intell. AI Games 6(2): 188-202 (2014) - [c62]Joshua K. Jones, Charles L. Isbell Jr.:
Story similarity measures for drama management with ttd-mdps. AAMAS 2014: 77-84 - [c61]Jonathan Scholz, Martin Levihn, Charles Lee Isbell Jr., David Wingate:
A Physics-Based Model Prior for Object-Oriented MDPs. ICML 2014: 1089-1097 - 2013
- [c60]Luis C. Cobo, Charles L. Isbell Jr., Andrea Lockerd Thomaz:
Object focused q-learning for autonomous agents. AAMAS 2013: 1061-1068 - [c59]Ryan R. Curtin, William B. March, Parikshit Ram, David V. Anderson, Alexander G. Gray, Charles L. Isbell Jr.:
Tree-Independent Dual-Tree Algorithms. ICML (3) 2013: 1435-1443 - [c58]Liam MacDermed, Charles L. Isbell Jr.:
Point Based Value Iteration with Optimal Belief Compression for Dec-POMDPs. NIPS 2013: 100-108 - [c57]Shane Griffith, Kaushik Subramanian, Jonathan Scholz, Charles L. Isbell Jr., Andrea Lockerd Thomaz:
Policy Shaping: Integrating Human Feedback with Reinforcement Learning. NIPS 2013: 2625-2633 - [i3]Ryan R. Curtin, William B. March, Parikshit Ram, David V. Anderson, Alexander G. Gray, Charles Lee Isbell Jr.:
Tree-Independent Dual-Tree Algorithms. CoRR abs/1304.4327 (2013) - 2012
- [j15]Joshua Letchford, Liam MacDermed, Vincent Conitzer, Ronald Parr, Charles L. Isbell Jr.:
Computing Stackelberg strategies in stochastic games. SIGecom Exch. 11(2): 36-40 (2012) - [c56]Joshua Letchford, Liam MacDermed, Vincent Conitzer, Ronald Parr, Charles L. Isbell Jr.:
Computing Optimal Strategies to Commit to in Stochastic Games. AAAI 2012: 1380-1386 - [c55]Luis C. Cobo, Charles Lee Isbell Jr., Andrea Lockerd Thomaz:
Automatic task decomposition and state abstraction from demonstration. AAMAS 2012: 483-490 - [i2]Michael P. Holmes, Alexander G. Gray, Charles Lee Isbell Jr.:
Fast Nonparametric Conditional Density Estimation. CoRR abs/1206.5278 (2012) - [i1]Rafay Hammid, Siddhartha Maddi, Amos Y. Johnson, Aaron F. Bobick, Irfan A. Essa, Charles Lee Isbell Jr.:
Unsupervised Activity Discovery and Characterization From Event-Streams. CoRR abs/1207.1381 (2012) - 2011
- [c54]Liam MacDermed, Charles L. Isbell Jr., Lora Weiss:
Markov Games of Incomplete Information for Multi-Agent Reinforcement Learning. Interactive Decision Theory and Game Theory 2011 - [c53]Liam MacDermed, Karthik Sankaran Narayan, Charles Lee Isbell Jr., Lora Weiss:
Quick Polytope Approximation of All Correlated Equilibria in Stochastic Games. AAAI 2011: 707-712 - [c52]Karthik Sankaran Narayan, Charles Lee Isbell Jr., David L. Roberts:
DEXTOR: Reduced Effort Authoring for Template-Based Natural Language Generation. AIIDE 2011 - [c51]Luis C. Cobo, Peng Zang, Charles Lee Isbell Jr., Andrea Lockerd Thomaz:
Automatic State Abstraction from Demonstration. IJCAI 2011: 1243-1248 - 2010
- [j14]David W. Aha, Mark S. Boddy, Vadim Bulitko, Artur S. d'Avila Garcez, Prashant Doshi, Stefan Edelkamp, Christopher W. Geib, Piotr J. Gmytrasiewicz, Robert P. Goldman, Pascal Hitzler, Charles L. Isbell Jr., Darsana P. Josyula, Leslie Pack Kaelbling, Kristian Kersting, Maithilee Kunda, Luís C. Lamb, Bhaskara Marthi, Keith McGreggor, Vivi Nastase, Gregory M. Provan, Anita Raja, Ashwin Ram, Mark O. Riedl, Stuart Russell, Ashish Sabharwal, Jan-Georg Smaus, Gita Sukthankar, Karl Tuyls, Ron van der Meyden, Alon Y. Halevy, Lilyana Mihalkova, Sriraam Natarajan:
Reports of the AAAI 2010 Conference Workshops. AI Mag. 31(4): 95-108 (2010) - [j13]Michael P. Holmes, Alexander G. Gray, Charles Lee Isbell Jr.:
Fast kernel conditional density estimation: A dual-tree Monte Carlo approach. Comput. Stat. Data Anal. 54(7): 1707-1718 (2010) - [c50]Peng Zang, Arya Irani, Peng Zhou, Charles Lee Isbell Jr., Andrea Lockerd Thomaz:
Using training regimens to teach expanding function approximators. AAMAS 2010: 341-348 - [c49]Peng Zang, Runhe Tian, Andrea Lockerd Thomaz, Charles L. Isbell Jr.:
Batch versus interactive learning by demonstration. ICDL 2010: 219-224
2000 – 2009
- 2009
- [j12]Raffay Hamid, Siddhartha Maddi, Amos Y. Johnson, Aaron F. Bobick, Irfan A. Essa, Charles Lee Isbell Jr.:
A novel sequence representation for unsupervised analysis of human activities. Artif. Intell. 173(14): 1221-1244 (2009) - [j11]Charles L. Isbell Jr., Lynn Andrea Stein, Robb Cutler, Jeffrey Forbes, Linda Fraser, John Impagliazzo, Viera K. Proulx, Steve Russ, Richard Thomas, Yan Xu:
(Re)defining computing curricula by (re)defining computing. ACM SIGCSE Bull. 41(4): 195-207 (2009) - [j10]Olufisayo Omojokun, Charles L. Isbell Jr., Prasun Dewan:
Towards automatic personalization of device controls. IEEE Trans. Consumer Electron. 55(1): 269-276 (2009) - [c48]David L. Roberts, Harikrishna Narayanan, Charles L. Isbell Jr.:
Learning to Influence Emotional Responses for Interactive Storytelling. AAAI Spring Symposium: Intelligent Narrative Technologies II 2009: 95-102 - [c47]David L. Roberts, Mark O. Riedl, Charles L. Isbell Jr.:
Beyond Adversarial: The Case for Game AI as Storytelling. DiGRA Conference 2009 - [c46]Peng Zang, Peng Zhou, David Minnen, Charles Lee Isbell Jr.:
Discovering options from example trajectories. ICML 2009: 1217-1224 - [c45]Liam Mac Dermed, Charles L. Isbell Jr.:
Solving Stochastic Games. NIPS 2009: 1186-1194 - [c44]David L. Roberts, Merrick L. Furst, Brian Dorn, Charles L. Isbell Jr.:
Using influence and persuasion to shape player experiences. Sandbox@SIGGRAPH 2009: 23-30 - 2008
- [j9]David L. Roberts, Charles L. Isbell Jr., Michael L. Littman:
Optimization problems involving collections of dependent objects. Ann. Oper. Res. 163(1): 255-270 (2008) - [c43]Rudolph L. Mappus IV, David Minnen, Charles Lee Isbell Jr.:
Dimensionality Reduction for Improved Source Separation in FMRI Data. BIOSIGNALS (2) 2008: 308-313 - [c42]David L. Roberts, Charles Lee Isbell Jr., Mark O. Riedl, Ian Bogost, Merrick L. Furst:
On the Use of Computational Models of Influence for Managing Interactive Virtual Experiences. ICIDS 2008: 268-272 - [c41]Olufisayo Omojokun, Michael Genovese, Charles Lee Isbell Jr.:
Impact of user context on song selection. ACM Multimedia 2008: 897-900 - [c40]Olufisayo Omojokun, Michael Genovese, Charles Lee Isbell Jr.:
Partial signal extraction for mobile media players. MoMM 2008: 282-286 - [c39]Michael P. Holmes, Alexander G. Gray, Charles Lee Isbell Jr.:
QUIC-SVD: Fast SVD Using Cosine Trees. NIPS 2008: 673-680 - [c38]Christopher L. Simpkins, Sooraj Bhat, Charles Lee Isbell Jr., Michael Mateas:
Towards adaptive programming: integrating reinforcement learning into a programming language. OOPSLA 2008: 603-614 - 2007
- [c37]David Minnen, Charles Lee Isbell Jr., Irfan A. Essa, Thad Starner:
Discovering Multivariate Motifs using Subsequence Density Estimation and Greedy Mixture Learning. AAAI 2007: 615-620 - [c36]David L. Roberts, Sooraj Bhat, Kenneth St. Clair, Charles Lee Isbell Jr.:
Authorial Idioms for Target Distributions in TTD-MDPs. AAAI 2007: 852-857 - [c35]David L. Roberts, Christina R. Strong, Charles L. Isbell Jr.:
Using Feature Value Distributions to Estimate Player Satisfaction through an Author's Eyes. AAAI Fall Symposium: Intelligent Narrative Technologies 2007: 119-126 - [c34]David L. Roberts, Andrew S. Cantino, Charles Lee Isbell Jr.:
Player Autonomy versus Designer Intent: A Case Study of Interactive Tour Guides. AIIDE 2007: 95-97 - [c33]Andrew S. Cantino, David L. Roberts, Charles L. Isbell Jr.:
Autonomous nondeterministic tour guides: improving quality of experience with TTD-MDPs. AAMAS 2007: 22 - [c32]Sooraj Bhat, David L. Roberts, Mark J. Nelson, Charles L. Isbell Jr., Michael Mateas:
A globally optimal algorithm for TTD-MDPs. AAMAS 2007: 199 - [c31]David Minnen, Charles L. Isbell Jr., Irfan A. Essa, Thad Starner:
Detecting Subdimensional Motifs: An Efficient Algorithm for Generalized Multivariate Pattern Discovery. ICDM 2007: 601-606 - [c30]Manu Sharma, Michael P. Holmes, Juan Carlos Santamaría, Arya Irani, Charles Lee Isbell Jr., Ashwin Ram:
Transfer Learning in Real-Time Strategy Games Using Hybrid CBR/RL. IJCAI 2007: 1041-1046 - [c29]Peng Zang, Charles Lee Isbell Jr.:
Managing Domain Knowledge and Multiple Models with Boosting. IJCAI 2007: 1144-1149 - [c28]David Minnen, Thad Starner, Irfan A. Essa, Charles Lee Isbell Jr.:
Improving Activity Discovery with Automatic Neighborhood Estimation. IJCAI 2007: 2814-2819 - [c27]Michael P. Holmes, Alexander G. Gray, Charles Lee Isbell Jr.:
Ultrafast Monte Carlo for Statistical Summations. NIPS 2007: 673-680 - [c26]Merrick L. Furst, Charles L. Isbell Jr., Mark Guzdial:
ThreadsTM: how to restructure a computer science curriculum for a flat world. SIGCSE 2007: 420-424 - [c25]Michael P. Holmes, Alexander G. Gray, Charles L. Isbell Jr.:
Fast Nonparametric Conditional Density Estimation. UAI 2007: 175-182 - 2006
- [j8]Charles Lee Isbell Jr., Michael J. Kearns, Satinder Singh, Christian R. Shelton, Peter Stone, David P. Kormann:
Cobot in LambdaMOO: An Adaptive Social Statistics Agent. Auton. Agents Multi Agent Syst. 13(3): 327-354 (2006) - [j7]Mark J. Nelson, Michael Mateas, David L. Roberts, Charles Lee Isbell Jr.:
Declarative Optimization-Based Drama Management in Interactive Fiction. IEEE Computer Graphics and Applications 26(3): 32-41 (2006) - [j6]Tucker R. Balch, Frank Dellaert, Adam Feldman, Andrew Guillory, Charles Lee Isbell Jr., Zia Khan, Stephen C. Pratt, Andrew N. Stein, Hank Wilde:
How Multirobot Systems Research will Accelerate our Understanding of Social Animal Behavior. Proc. IEEE 94(7): 1445-1463 (2006) - [j5]Olufisayo Omojokun, Jeffrey S. Pierce, Charles Lee Isbell Jr., Prasun Dewan:
Comparing end-user and intelligent remote control interface generation. Pers. Ubiquitous Comput. 10(2-3): 136-143 (2006) - [c24]Sooraj Bhat, Charles Lee Isbell Jr., Michael Mateas:
On the Difficulty of Modular Reinforcement Learning for Real-World Partial Programming. AAAI 2006: 318-323 - [c23]Kevin Quennesson, Elias Ioup, Charles L. Isbell Jr.:
Wavelet Statistics for Human Motion Classification. AAAI 2006 - [c22]David L. Roberts, Mark J. Nelson, Charles Lee Isbell Jr., Michael Mateas, Michael L. Littman:
Targeting Specific Distributions of Trajectories in MDPs. AAAI 2006: 1213-1218 - [c21]David L. Roberts, Sooraj Bhat, Charles Lee Isbell Jr., Brian F. Cooper, Jeffrey S. Pierce:
A decision-theoretic approach to file consistency in constrained peer-to-peer device networks. AAMAS 2006: 338-340 - [c20]Mark J. Nelson, David L. Roberts, Charles Lee Isbell Jr., Michael Mateas:
Reinforcement learning for declarative optimization-based drama management. AAMAS 2006: 775-782 - [c19]Andrew Guillory, Hai Nguyen, Tucker R. Balch, Charles Lee Isbell Jr.:
Learning executable agent behaviors from observation. AAMAS 2006: 795-797 - [c18]Michael P. Holmes, Charles Lee Isbell Jr.:
Looping suffix tree-based inference of partially observable hidden state. ICML 2006: 409-416 - [c17]David Minnen, Thad Starner, Irfan A. Essa, Charles Lee Isbell Jr.:
Discovering Characteristic Actions from On-Body Sensor Data. ISWC 2006: 11-18 - 2005
- [c16]Raffay Hamid, Amos Y. Johnson, Samir Batta, Aaron F. Bobick, Charles L. Isbell Jr., Graham Coleman:
Detection and Explanation of Anomalous Activities: Representing Activities as Bags of Event n-Grams. CVPR (1) 2005: 1031-1038 - [c15]Rafay Hammid, Siddhartha Maddi, Amos Y. Johnson, Aaron F. Bobick, Irfan A. Essa, Charles Lee Isbell Jr.:
Unsupervised Activity Discovery and Characterization From Event-Streams. UAI 2005: 251-258 - 2004
- [j4]Charles L. Isbell Jr., Olufisayo Omojokun, Jeffrey S. Pierce:
From devices to tasks: automatic task prediction for personalized appliance control. Pers. Ubiquitous Comput. 8(3-4): 146-153 (2004) - [j3]Brian M. Landry, Jeffrey S. Pierce, Charles L. Isbell Jr.:
Supporting routine decision-making with a next-generation alarm clock. Pers. Ubiquitous Comput. 8(3-4): 154-160 (2004) - [c14]Michael P. Holmes, Charles Lee Isbell Jr.:
Schema Learning: Experience-Based Construction of Predictive Action Models. NIPS 2004: 585-592 - 2003
- [j2]Yukio Ohsawa, Peter McBurney, Simon Parsons, Christopher A. Miller, Alan C. Schultz, Jean Scholtz, Michael A. Goodrich, Eugene Santos Jr., Benjamin Bell, Charles Lee Isbell Jr., Michael L. Littman:
AAAI-2002 Fall Symposium Series. AI Mag. 24(1): 95-98 (2003) - [c13]Olufisayo Omojokun, Charles Lee Isbell Jr.:
User modeling for personalized universal appliance interaction. Richard Tapia Celebration of Diversity in Computing Conference 2003: 65-68 - 2002
- [c12]Michael J. Kearns, Charles Lee Isbell Jr., Satinder Singh, Diane J. Litman, Jessica Howe:
CobotDS: A Spoken Dialogue System for Chat. AAAI/IAAI 2002: 425-430 - [c11]Lawrence K. Saul, Daniel D. Lee, Charles L. Isbell Jr., Yann LeCun:
Real Time Voice Processing with Audiovisual Feedback: Toward Autonomous Agents with Perfect Pitch. NIPS 2002: 1181-1188 - 2001
- [c10]Charles Lee Isbell Jr., Christian R. Shelton, Michael J. Kearns, Satinder Singh, Peter Stone:
A social reinforcement learning agent. Agents 2001: 377-384 - [c9]Charles Lee Isbell Jr., Christian R. Shelton, Michael J. Kearns, Satinder Singh, Peter Stone:
Cobot: A Social Reinforcement Learning Agent. NIPS 2001: 1393-1400 - 2000
- [c8]Charles Lee Isbell Jr., Michael J. Kearns, David P. Kormann, Satinder Singh, Peter Stone:
Cobot in LambdaMOO: A Social Statistics Agent. AAAI/IAAI 2000: 36-41
1990 – 1999
- 1999
- [c7]Charles Lee Isbell Jr., Parry Husbands:
The Parallel Problems Server: an Interactive Tool for Large Scale Machine Learning. NIPS 1999: 703-709 - [c6]Parry Husbands, Charles Lee Isbell Jr., Alan Edelman:
MITMatlab: A Tool for Interactive Supercomputing. PP 1999 - 1998
- [b1]Charles L. Isbell Jr.:
Sparse multi-level representations for text retrieval. Massachusetts Institute of Technology, Cambridge, MA, USA, 1998 - [j1]Deborah L. McGuinness, Charles L. Isbell Jr., Matt Parker, Peter F. Patel-Schneider, Lori Alperin Resnick, Christopher A. Welty:
A description logic-based configurator on the web. SIGART Bull. 9(2): 20-22 (1998) - [c5]Charles Lee Isbell Jr., Paul A. Viola:
Restructuring Sparse High Dimensional Data for Effective Retrieval. NIPS 1998: 480-486 - [c4]Parry Husbands, Charles Lee Isbell Jr.:
The Parallel Problems Server: A Client-Server Model for Interactive Large Scale Scientific Computation. VECPAR 1998: 156-169 - 1996
- [c3]Alexander Borgida, Charles L. Isbell Jr., Deborah L. McGuinness:
Reasoning with Black Boxes: Handling Test Concepts in CLASSIC. Description Logics 1996: 87-91 - [c2]Jeremy S. De Bonet, Charles Lee Isbell Jr., Paul A. Viola:
MIMIC: Finding Optima by Estimating Probability Densities. NIPS 1996: 424-430 - 1995
- [c1]Deborah L. McGuinness, Lori Alperin Resnick, Charles Lee Isbell Jr.:
Description Logic in Practice: A CLASSIC Application. IJCAI 1995: 2045-2046
Coauthor Index
Andrea Thomaz
aka: Andrea Lockerd Thomaz
aka: Andrea Lockerd Thomaz
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