 | 2010 |
|---|
| 9 |       | Thomas J. Walsh,
Kaushik Subramanian,
Michael L. Littman,
Carlos Diuk:
Generalizing Apprenticeship Learning across Hypothesis Classes.
ICML 2010: 1119-1126 |
| 2009 |
|---|
| 8 | | David Wingate,
Carlos Diuk,
Lihong Li,
Matthew Taylor,
Jordan Frank:
Workshop summary: Results of the 2009 reinforcement learning competition.
ICML 2009: 166 |
| 7 | | Carlos Diuk,
Lihong Li,
Bethany R. Leffler:
The adaptive k-meteorologists problem and its application to structure learning and feature selection in reinforcement learning.
ICML 2009: 32 |
| 6 | | Thomas J. Walsh,
Istvan Szita,
Carlos Diuk,
Michael L. Littman:
Exploring compact reinforcement-learning representations with linear regression.
UAI 2009: 591-598 |
| 5 | | Carlos Diuk,
Michael L. Littman:
Hierarchical Reinforcement Learning.
Encyclopedia of Artificial Intelligence 2009: 825-830 |
| 2008 |
|---|
| 4 | | Carlos Diuk,
Andre Cohen,
Michael L. Littman:
An object-oriented representation for efficient reinforcement learning.
ICML 2008: 240-247 |
| 2007 |
|---|
| 3 |  | Alexander L. Strehl,
Carlos Diuk,
Michael L. Littman:
Efficient Structure Learning in Factored-State MDPs.
AAAI 2007: 645-650 |
| 2006 |
|---|
| 2 | | Carlos Diuk,
Michael L. Littman:
A Change Detection Model for Non-Stationary k-Armed Bandit Problems.
AAAI Spring Symposium: Between a Rock and a Hard Place: Cognitive Science Principles Meet AI-Hard Problems 2006: 39 |
| 1 | | Carlos Diuk,
Alexander L. Strehl,
Michael L. Littman:
A hierarchical approach to efficient reinforcement learning in deterministic domains.
AAMAS 2006: 313-319 |
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