Qualitative reinforcement learning

ACM International Conference Proceeding Series

Volumn 148, Issue , 2006, Pages 305-312

  Epshteyn, Arkady ^a   DeJong, Gerald ^a  

^a University of Illinois at Urbana Champaign   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; MARKOV PROCESSES; PROBABILITY; PROBLEM SOLVING; STOCHASTIC MODELS;

STOCHASTIC DOMINANCE CONSTRAINTS; TRANSITION PROBABILITIES;

REINFORCEMENT LEARNING;

EID: 34250717446     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1143844.1143883     Document Type: Conference Paper

References (10)

1. Abbeel, P., & Ng, A. Y. (2004). Apprenticeship learning via inverse reinforcement learning. ICML.
2. Abbeel, P., & Ng, A. Y. (2005). Exploration and apprenticeship learning in reinforcement learning. ICML.
3. Bonet, B., & Pearl, J. (2002). Qualitative mdps and pomdps: An order-of-magnitude approximation. UAI.
4. Epshteyn, A., & DeJong, G. (2006). Qualitative reinforcement learning (full paper). http://www.ews.uiuc.edu/~aepshtey/pubs/qual_rl.ps.
5. Givan, R., Leach, S., & Dean, T. (2000). Bounded-parameter markov decision processes. Artificial Intelligence, 122, 71-109.
6. Laud, A., & DeJong, G. (2003). The influence of reward on the speed of reinforcement learning: An analysis of shaping. ICML.
7. Ng, A. Y., Harada, D., & Russell, S. J. (1999). Policy invariance under reward transformations: Theory and application to reward shaping. ICML.
8. Sabbadin, R. (1999). A possibilistic model for qualitative sequential decision problems under uncertainty in partially observable environments. UAI
9. Shaked, M., & Shanthikumar, J. G. (1994). Stochastic orders and their applications. San Diego, CA: Academic Press.
10. Sutton, R. S., & Barto, A. G. (1998). Reinforcement learning: An introduction. Cambridge, MA: MIT Press.