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Semantic Scholar9. EWRL 2011: Athens, Greece
Scott Sanner, Marcus Hutter:
Recent Advances in Reinforcement Learning - 9th European Workshop, EWRL 2011, Athens, Greece, September 9-11, 2011, Revised Selected Papers. Lecture Notes in Computer Science 7188, Springer 2012, ISBN 978-3-642-29945-2
Invited Talk Abstracts
- Kristian Kersting:
Invited Talk: Increasing Representational Power and Scaling Inference in Reinforcement Learning. 2 - Peter Stone:
Invited Talk: PRISM - Practical RL: Representation, Interaction, Synthesis, and Mortality. 3
Online Reinforcement Learning
- Francis Maes, Louis Wehenkel, Damien Ernst:
Automatic Discovery of Ranking Formulas for Playing with Multi-armed Bandits. 5-17 - Sylvie C. W. Ong, Yuri Grinberg, Joelle Pineau:
Goal-Directed Online Learning of Predictive Models. 18-29 - Matthew W. Robards, Peter Sunehag:
Gradient Based Algorithms with Loss Functions and Kernels for Improved On-Policy Control. 30-41
Learning and Exploring MDPs
- Mauricio Araya-López, Olivier Buffet, Vincent Thomas, François Charpillet:
Active Learning of MDP Models. 42-53
Function Approximation Methods for Reinforcement Learning
- Matthew W. Hoffman, Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos:
Regularized Least Squares Temporal Difference Learning with Nested ℓ2 and ℓ1 Penalization. 102-114 - Nikolaos Tziortziotis, Konstantinos Blekas:
Value Function Approximation through Sparse Bayesian Modeling. 128-139
Macro-actions in Reinforcement Learning
- Pablo Samuel Castro, Doina Precup:
Automatic Construction of Temporally Extended Actions for MDPs Using Bisimulation Metrics. 140-152 - Kfir Y. Levy, Nahum Shimkin:
Unified Inter and Intra Options Learning Using Policy Gradient Methods. 153-164
Policy Search and Bounds
- Cosmin Paduraru, Doina Precup, Joelle Pineau:
A Framework for Computing Bounds for the Return of a Policy. 201-212
Multi-Task and Transfer Reinforcement Learning
- Kyriakos C. Chatzidimitriou, Ioannis Partalas, Pericles A. Mitkas, Ioannis P. Vlahavas:
Transferring Evolved Reservoir Features in Reinforcement Learning Tasks. 213-224 - Anestis Fachantidis, Ioannis Partalas, Matthew E. Taylor, Ioannis P. Vlahavas:
Transfer Learning via Multiple Inter-task Mappings. 225-236 - Matthijs Snel, Shimon Whiteson:
Multi-Task Reinforcement Learning: Shaping and Feature Selection. 237-248
Multi-Agent Reinforcement Learning
- Georgios Boutsioukis, Ioannis Partalas, Ioannis P. Vlahavas:
Transfer Learning in Multi-Agent Reinforcement Learning Domains. 249-260 - Ioannis Lambrou, Vassilis Vassiliades, Chris Christodoulou:
An Extension of a Hierarchical Reinforcement Learning Algorithm for Multiagent Settings. 261-272
Apprenticeship and Inverse Reinforcement Learning
- Christos Dimitrakakis, Constantin A. Rothkopf:
Bayesian Multitask Inverse Reinforcement Learning. 273-284 - Edouard Klein, Matthieu Geist, Olivier Pietquin:
Batch, Off-Policy and Model-Free Apprenticeship Learning. 285-296
Real-World Reinforcement Learning
- Seiya Kuroda, Kazuteru Miyazaki, Hiroaki Kobayashi:
Introduction of Fixed Mode States into Online Profit Sharing and Its Application to Waist Trajectory Generation of Biped Robot. 297-308 - Tohgoroh Matsui, Takashi Goto, Kiyoshi Izumi, Yu Chen:
Compound Reinforcement Learning: Theory and an Application to Finance. 321-332 - Kazuteru Miyazaki, Masaaki Ida:
Proposal and Evaluation of the Active Course Classification Support System with Exploitation-Oriented Learning. 333-344
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