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James MacGlashan
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2020 – today
- 2022
- [j3]Peter R. Wurman
, Samuel Barrett, Kenta Kawamoto, James MacGlashan, Kaushik Subramanian, Thomas J. Walsh, Roberto Capobianco
, Alisa Devlic, Franziska Eckert, Florian Fuchs
, Leilani Gilpin
, Piyush Khandelwal, Varun Raj Kompella, HaoChih Lin, Patrick MacAlpine, Declan Oller, Takuma Seno, Craig Sherstan, Michael D. Thomure, Houmehr Aghabozorgi, Leon Barrett
, Rory Douglas, Dion Whitehead, Peter Dürr
, Peter Stone, Michael Spranger
, Hiroaki Kitano
:
Outracing champion Gran Turismo drivers with deep reinforcement learning. Nat. 602(7896): 223-228 (2022) - [c28]James MacGlashan, Evan Archer, Alisa Devlic, Takuma Seno, Craig Sherstan, Peter R. Wurman, Peter Stone:
Value Function Decomposition for Iterative Design of Reinforcement Learning Agents. NeurIPS 2022 - [i5]James MacGlashan, Evan Archer, Alisa Devlic, Takuma Seno, Craig Sherstan, Peter R. Wurman, Peter Stone:
Value Function Decomposition for Iterative Design of Reinforcement Learning Agents. CoRR abs/2206.13901 (2022) - 2021
- [c27]Piyush Khandelwal, James MacGlashan, Peter R. Wurman, Peter Stone:
Efficient Real-Time Inference in Temporal Convolution Networks. ICRA 2021: 13489-13495 - 2020
- [c26]Craig Sherstan, Shibhansh Dohare, James MacGlashan, Johannes Günther, Patrick M. Pilarski:
Gamma-Nets: Generalizing Value Estimation over Timescale. AAAI 2020: 5717-5725
2010 – 2019
- 2019
- [i4]Craig Sherstan, Shibhansh Dohare, James MacGlashan, Johannes Günther, Patrick M. Pilarski:
Gamma-Nets: Generalizing Value Estimation over Timescale. CoRR abs/1911.07794 (2019) - 2018
- [j2]Bei Peng
, James MacGlashan, Robert Tyler Loftin
, Michael L. Littman, David L. Roberts
, Matthew E. Taylor
:
Curriculum Design for Machine Learners in Sequential Decision Tasks. IEEE Trans. Emerg. Top. Comput. Intell. 2(4): 268-277 (2018) - 2017
- [c25]Nakul Gopalan, Marie desJardins, Michael L. Littman, James MacGlashan, Shawn Squire, Stefanie Tellex, John Winder, Lawson L. S. Wong:
Planning with Abstract Markov Decision Processes. ICAPS 2017: 480-488 - [c24]Bei Peng, James MacGlashan, Robert T. Loftin, Michael L. Littman, David L. Roberts, Matthew E. Taylor:
Curriculum Design for Machine Learners in Sequential Decision Tasks. AAMAS 2017: 1682-1684 - [c23]James MacGlashan, Mark K. Ho, Robert Tyler Loftin, Bei Peng, Guan Wang, David L. Roberts, Matthew E. Taylor, Michael L. Littman:
Interactive Learning from Policy-Dependent Human Feedback. ICML 2017: 2285-2294 - [c22]David Whitney, Eric Rosen, James MacGlashan, Lawson L. S. Wong, Stefanie Tellex:
Reducing errors in object-fetching interactions through social feedback. ICRA 2017: 1006-1013 - [i3]James MacGlashan, Mark K. Ho, Robert Tyler Loftin, Bei Peng, David L. Roberts, Matthew E. Taylor, Michael L. Littman:
Interactive Learning from Policy-Dependent Human Feedback. CoRR abs/1701.06049 (2017) - [i2]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) - [i1]Melrose Roderick, James MacGlashan, Stefanie Tellex:
Implementing the Deep Q-Network. CoRR abs/1711.07478 (2017) - 2016
- [j1]Robert T. Loftin
, Bei Peng, James MacGlashan, Michael L. Littman, Matthew E. Taylor
, Jeff Huang, David L. Roberts:
Learning behaviors via human-delivered discrete feedback: modeling implicit feedback strategies to speed up learning. Auton. Agents Multi Agent Syst. 30(1): 30-59 (2016) - [c21]David Abel, James MacGlashan, Michael L. Littman:
Reinforcement Learning as a Framework for Ethical Decision Making. AAAI Workshop: AI, Ethics, and Society 2016 - [c20]Robert Tyler Loftin, James MacGlashan, Bei Peng, Matthew E. Taylor, Michael L. Littman, David L. Roberts:
Towards Behavior-Aware Model Learning from Human-Generated Trajectories. AAAI Fall Symposia 2016 - [c19]Bei Peng, James MacGlashan, Robert Tyler Loftin, Michael L. Littman, David L. Roberts, Matthew E. Taylor:
A Need for Speed: Adapting Agent Action Speed to Improve Task Learning from Non-Expert Humans. AAMAS 2016: 957-965 - [c18]Mark K. Ho, James MacGlashan, Amy Greenwald, Michael L. Littman, Elizabeth Hilliard, Carl Trimbach, Stephen Brawner, Josh Tenenbaum, Max Kleiman-Weiner, Joseph L. Austerweil:
Feature-based Joint Planning and Norm Learning in Collaborative Games. CogSci 2016 - [c17]Mark K. Ho, Michael L. Littman, James MacGlashan, Fiery Cushman, Joseph L. Austerweil:
Showing versus doing: Teaching by demonstration. NIPS 2016: 3027-3035 - 2015
- [c16]Krishna Chaitanya Aluru, Stefanie Tellex, John Oberlin, James MacGlashan:
Minecraft as an Experimental World for AI in Robotics. AAAI Fall Symposia 2015: 5-12 - [c15]David Ellis Hershkowitz, James MacGlashan, Stefanie Tellex:
Learning Propositional Functions for Planning and Reinforcement Learning. AAAI Fall Symposia 2015: 38-45 - [c14]Emily Wu, Yuxin Han, David Whitney, John Oberlin, James MacGlashan, Stefanie Tellex:
Robotic Social Feedback for Object Specification. AAAI Fall Symposia 2015: 150-157 - [c13]David Abel, D. Ellis Hershkowitz, Gabriel Barth-Maron, Stephen Brawner, Kevin O'Farrell, James MacGlashan, Stefanie Tellex:
Goal-Based Action Priors. ICAPS 2015: 306-314 - [c12]James MacGlashan, Michael L. Littman:
Between Imitation and Intention Learning. IJCAI 2015: 3692-3698 - [c11]Nicholay Topin, Nicholas Haltmeyer, Shawn Squire, John Winder, Marie desJardins, James MacGlashan:
Portable Option Discovery for Automated Learning Transfer in Object-Oriented Markov Decision Processes. IJCAI 2015: 3856-3864 - [c10]James MacGlashan, Monica Babes-Vroman, Marie desJardins, Michael L. Littman, Smaranda Muresan, Shawn Squire, Stefanie Tellex, Dilip Arumugam, Lei Yang:
Grounding English Commands to Reward Functions. Robotics: Science and Systems 2015 - 2014
- [c9]Robert Tyler Loftin, James MacGlashan, Bei Peng, Matthew E. Taylor, Michael L. Littman, Jeff Huang, David L. Roberts:
A Strategy-Aware Technique for Learning Behaviors from Discrete Human Feedback. AAAI 2014: 937-943 - [c8]Gabriel Barth-Maron, David Abel, James MacGlashan, Stefanie Tellex:
Affordances as Transferable Knowledge for Planning Agents. AAAI Fall Symposia 2014 - [c7]Marie desJardins, Tenji Tembo, Nicholay Topin, Michael Bishoff, Shawn Squire, James MacGlashan, Rose Carignan, Nicholas Haltmeyer:
Discovering Subgoals in Complex Domains. AAAI Fall Symposia 2014 - [c6]James MacGlashan, Michael L. Littman, Fiery Cushman:
Flexible theft and resolute punishment: Evolutionary dynamics of social behavior among reinforcement-learning agents. CogSci 2014 - [c5]Robert Tyler Loftin, Bei Peng, James MacGlashan, Michael L. Littman, Matthew E. Taylor
, Jeff Huang, David L. Roberts:
Learning something from nothing: Leveraging implicit human feedback strategies. RO-MAN 2014: 607-612 - 2010
- [c4]James MacGlashan:
Hierarchical Skill Learning for High-Level Planning. AAAI 2010 - [c3]James MacGlashan, Don Miner, Marie desJardins:
A Game Playing System for Use in Computer Science Education. FLAIRS 2010 - [c2]Marie desJardins, James MacGlashan, Kiri L. Wagstaff
:
Confidence-Based Feature Acquisition to Minimize Training and Test Costs. SDM 2010: 514-524
2000 – 2009
- 2007
- [c1]Marie desJardins, James MacGlashan, Julia Ferraioli
:
Interactive visual clustering. IUI 2007: 361-364
Coauthor Index
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