Volume 84, Numbers 1-2, July 2011

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  Shimon Whiteson, Michael L. Littman: Introduction to the special issue on empirical evaluations in reinforcement learning. 1-6
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  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 Riedmiller: Reinforcement learning in feedback control - Challenges and benchmarks from technical process control. 137-169
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  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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