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ORCIDMachine Learning, Volume 84
Volume 84, Numbers 1-2, July 2011
- Shimon Whiteson, Michael L. Littman:
Introduction to the special issue on empirical evaluations in reinforcement learning. 1-6 - Tim Kovacs, Robert Egginton:
On the analysis and design of software for reinforcement learning, with a survey of existing systems. 7-49 - Peter Vamplew
, Richard Dazeley, Adam Berry, Rustam Issabekov, Evan Dekker:
Empirical evaluation methods for multiobjective reinforcement learning algorithms. 51-80 - Alan Fern, Roni Khardon, Prasad Tadepalli:
The first learning track of the international planning competition. 81-107 - Susan M. Shortreed, Eric B. Laber, Daniel J. Lizotte, T. Scott Stroup, Joelle Pineau, Susan A. Murphy:
Informing sequential clinical decision-making through reinforcement learning: an empirical study. 109-136 - Roland Hafner, Martin A. Riedmiller:
Reinforcement learning in feedback control - Challenges and benchmarks from technical process control. 137-169 - Jens Kober, Jan Peters:
Policy search for motor primitives in robotics. 171-203 - Shivaram Kalyanakrishnan, Peter Stone:
Characterizing reinforcement learning methods through parameterized learning problems. 205-247
Volume 84, Number 3, September 2011
- Chris D. Bartels, Jeff A. Bilmes:
Creating non-minimal triangulations for use in inference in mixed stochastic/deterministic graphical models. 249-289 - Sanjay Jain, Efim B. Kinber:
Iterative learning from texts and counterexamples using additional information. 291-333 - Amy McGovern, Kiri L. Wagstaff:
Machine learning in space: extending our reach. 335-340 - Michael C. Burl, Philipp Georg Wetzler:
Onboard object recognition for planetary exploration. 341-367
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