by Adam White                              

5. A Recurrent Neural Network Acquires Working Memory Properties by Reward-dependent STDP  
    by Cristina Savin, Jochen Triesch                          

6. Acting With Confidence:  Quantifying Policy Uncertainty for Medical Applications
    by Daniel J. Lizotte, Eric Laber, Susan Murphy                      

7. An Algorithm for the Associative Reinforcement Learning Problem   
    by Gabor Bartok, Csaba Szepesvari                          

8. An Empirical Comparison of Techniques for Learning Models of Markov Decision Processes   
    by Todd Hester, Peter Stone                          

9. Application of New Temporal Difference Learning Methods for Approximate Solution of Large Linear Systems   
    by Hamid R. Maei, Richard S. Sutton, Csaba Szepesvari                      

10. Applying Reinforcement Learning to Modular Cooperative Robotic Systems   
    by Javier de Lope, Jose Antonio Martin H., Dario Maravall                      

11. Bayesian Inference for Efficient Learning in Control   
    by Marc Peter Deisenroth, Carl Edward Rasmussen                          

12. Can Reinforcement Learning provide a Unifying Framework for the Etiology of Dystonia?   
    by David A Peterson, Terrence Sejnowski, Howard Poizner                      

13. Categorizing Transfer for Reinforcement Learning   

    by Matthew E. Taylor, Peter Stone                          

14. Context Dependent, Model-based Reinforcement Learning Explains to Reward Devaluation Over Time   
    by Trent Toulouse, Suzanna Becker                          

15. Division of labor among multiple parallel cortico-basal ganglia-thalamic loops in pavlovian and instrumental tasks: A biologically-based computational model   
    by Wolfgang M. Pauli, Thomas E. Hazy, Randall C. O'Reilly     

    by Jeremy J. Clark, Shelly B. Flagel, Scott B. Evans, Christina A. Akers, Sarah M. Clinton, Ingo                     Willuhn, Terry E. Robinson, Huda Akil, Paul E.M. Phillips                 

17. Dynamic Portfolio Management with Transaction Costs   
    by Alberto Suarez, John Moody, Matthew Saffell                                  

18. Encoding Sequences of Spikes in Spiking Neural Networks through Reinforcement Learning   
    by Filip Ponulak, Stefan Rotter                          

19. Exploiting Training Regimens to Improve Learning   
    by Peng Zang, Charles Isbell, Andrea Thomaz                      

20. Feature Selection for Value Function Approximation Using Bayesian Model Selection   
    by Tobias Jung, Peter Stone                          

21. How Perceptual Categories Influence Trial and Error Learning in Humans   
    by John McDonnell, Todd M. Gureckis                          

22. Human Decision Making Under Uncertainty And The Need To Dissociate Mean-Variance Analysis And Expected Utility Theory   
    by Mathieu d'Acremont, Peter Bossaerts                          

23. Improving Bayesian Reinforcement Learning Using Transition Abstraction   

    by Daniel Acuna, Paul Schrater                          

24. Integrating Value Function-Based and Policy Search Methods for Sequential Decision Making 

    by Shivaram Kalyanakrishnan, Peter Stone                          

25. Knows What It Knows: A framework for Self-Aware Learning  
    by Lihong Li, Michael L. Littman, Thomas J. Walsh                      

26. Knowledge Representation for Autonomous Robotics   
    by Anna Koop, Marc G. Bellemare                          

27. Learning a Successful Emotional Interaction with an Artificial Partner  
    by Isabella Cattinelli, Massimiliano Goldwurm, N. Alberto Borghese                      

28. Learning Approximate Predictive Representations   
    by Monica Dinculescu                              

29. Learning in Uncertain Environments: Comparing Human and Macaque Reinforcement Learning Against an Optimal Benchmark and Quantitatively Measuring Reward Prediction Error in BOLD   
    by E. J. DeWitt, M. Dean, P. W. Glimcher                      

30. Learning State Space Models from Time Series Data   
    by Jordan Frank                              

31. Linear Value Function Approximation and Linear Models   
    by Ronald Parr, Gavin Taylor, Christopher Painter-Wakefield, Lihong Li, Michael Littman              

32. Model-based Bayesian Reinforcement Learning with Adaptive State Aggregation   
    by Cosmin Paduraru, Arthur Guez, Doina Precup, Joelle Pineau  

33. Non-disjoint modularity in reinforcement learning through boosted policies
    by Kurt Driessens               

34. Online Learning in Markov Decision Processes with Arbitratily Changing Rewards and Transitions

    by Jia Yuan Yu, Shie Mannor                          

35. Online TD(1) Meets Offline Monte Carlo   
    by Yao-Liang Yu, Yongjian Zhang, Csaba Szepesvari                      

36. Optimal Human Reinforcement Learning in a Hierarchical Decision Task   
    by Ulrik Beierholm, Klaus Wunderlich, Peter Bossaerts, John P O'Doherty                  

37. Optimal Online Learning Procedures for Model-Free Policy Evaluation   
    by Tshuyoshi Ueno, Shin-ichi Maeda, Motoaki Kawanabe, Shin Ishii                  

38. PAC-MDP Reinforcement Learning with Bayesian Priors   
    by John Asmuth, Lihong Li, Michael L. Littman, Ali Nouri, David Wingate              

39. Parametric Regret in Uncertain Markov Decision Processes   
    by Huan Xu, Shie Mannor                          

40. Personalized Intelligent Tutoring System Using Reinforcement Learning   
    by Ankit Malpani, B. Ravindran, Hema A. Murthy                      

41. Probabilistic Discounting for Modeling Behaviors in Iowa Gambling Task    
    by Takaki Makino, Taiki Takahashi, Hirofumi Nishinaka, Hiroki Fukui                  

42. Regularization in Reinforcement Learning   
    by Amir massoud Farahmand, Mohammad Ghavamzadeh, Csaba Szepesvari, Shie Mannor             

43. Reinforcement Learning for Computational Finance   
    by Yuxi Li, Csaba Szepesvari, Dale Schuurmans                      

44. Reinforcement Learning Rules for Spiking Neurons Can Learn Spatiotemporal Activity Patterns   

    by Nicolas Fremaux, Wulfram Gerstner                          

45. RL-Glue: From Grid Worlds to Sensor Rich Robots   
    by Brian Tanner, Adam White, Richard Sutton                      

46. Robot Navigation Based On Ego Perspective Images   
    by Wendelin Böhmer, Steffen Grünewälder, Klaus Obermayer                      

47. Skill Chaining: Skill Discovery in Continuous Domains  
    by George Konidaris, Andrew Barto                          

48. Spike-based Reinforcement Learning in Continuous State and Action Space   
    by Eleni Vasilaki, Robert Urbanczik, Walter Senn, Wulfram Gerstner                  

49. Temporal Difference Learning by Direct Preconditioning   
    by Hengshuai Yao, Shalabh Bhatnagar, Csaba Szepesvari                      

50. The BRIO Labyrinth Game - A Testbed for Reinforcement Learning and for Studies on Sensorimotor Learning   
    by Jan Hendrik Metzen, Elsa Kirchner, Larbi Abdenebaoui, Frank Kirchner                  

51. The Critterbot:  A Subjective Robotic Project  
    by M. Bellemare, M. Bowling, T. Degris, A. Koop, C. Rayner, M. Sokolsky, R. Sutton, A. White, E. Wiewiora

52. The Impact of Perceptual Aliasing on Human Learning in a Dynamic Decision Making Task   
    by Lisa Zaval, Louis Tur, Todd M. Gureckis
                     
53. The RLAI Robotic Simulator   
    by Marc G. Bellemare
                              
54. The Role of Basal Ganglia in Performing Simple Reaching Movements:  A Computational Model            by Madgoom Mohamed, V. S. Chakravarthy, Deepak Subramanian, B. Ravindran         
        
55. Timing in Reinforcement Learning Models of Classical Conditioning
    by Elliot A. Ludvig, Richard S. Sutton, E. James Kehoe.

56. Towards Autonomous Reinforcement Learning for Self-Adaptive Gas Turbine Control   
    by Alexander Hans, Steffen Udluft   
                     
57. Unmasking Neurostimulation Policies for the Treatment of Epilepsy  
    by Keith Bush, Joelle Pineau, Massimo Avoli    
                 
58. Using Batch RL to Optimize Neurostimulation Strategies  
    by Arthur Guez, Joelle Pineau                      
   
59. Value Function Approximation using the Fourier Basis   
    by George Konidaris, Sarah Osentoski   
                      
60. Variable-metric Evolution Strategies for Direct Policy Search   
    by Verena Heidrich-Meisner, Christian Igel

These accepted posters will not be presented at the symposium:

Automatic Subgoals Discovering Method With State Abstraction In Reinforcement Learning   
    by Marek Lapko, Rudolf Jaksa and Peter Sincak

Coordinated Learning in Infinite Markov Games   
    by Francisco S. Melo                              

Efficient Reinforcement Learning in Parameterized Models: The Parameter Elimination Approach   
    by Kirill Dyagilev, Shie Mannor, Nahum Shimkin  

Reinforcement Learning and Affective Response to Consumer Environments   
    by Gordon R. Foxall, Mirella Yani-de-Soriano