Predictive State Representation
- Predictive State Representation
In computer science, a Predictive State Representation (PSR) is a dynamical system representation that keeps track of the state of the system using predictions of future observations. A PSR's state is grounded directly to statistics over observable quantities. This is in contrast to other models of dynamical systems, such as Partially observable Markov decision processes (POMDPs) where the state of the system is represented as a probability distribution over unobserved nominal states.
References
* cite conference
last = Littman | first = Michael L. | authorlink = Michael L. Littman
coauthors = Richard S. Sutton; Satinder Singh
title = Predictive Representations of State
booktitle = Advances in Neural Information Processing Systems 14 (NIPS)
pages = 1555 - 1561
year = 2002
url = http://www.eecs.umich.edu/~baveja/Papers/psr.pdf
* cite conference
last =Singh | first = Satinder
coauthors = Michael R. James; Matthew R. Rudary
title = Predictive State Representations: A New Theory for Modeling Dynamical Systems
booktitle = Uncertainty in Artificial Intelligence: Proceedings of the Twentieth Conference (UAI)
pages = 512-519
year = 2004
url = http://www.eecs.umich.edu/~baveja/Papers/uai2004psr.pdf
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