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AAAI
2006
14 years 11 months ago
Improving Approximate Value Iteration Using Memories and Predictive State Representations
Planning in partially-observable dynamical systems is a challenging problem, and recent developments in point-based techniques such as Perseus significantly improve performance as...
Michael R. James, Ton Wessling, Nikos A. Vlassis
ICML
2008
IEEE
15 years 11 months ago
Efficiently learning linear-linear exponential family predictive representations of state
Exponential Family PSR (EFPSR) models capture stochastic dynamical systems by representing state as the parameters of an exponential family distribution over a shortterm window of...
David Wingate, Satinder P. Singh
98
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ATAL
2010
Springer
14 years 11 months ago
Closing the learning-planning loop with predictive state representations
A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...
Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon
66
Voted
AAAI
2007
15 years 19 days ago
Abstraction in Predictive State Representations
Vishal Soni, Satinder P. Singh
71
Voted
IJCAI
2007
14 years 11 months ago
Grounding Abstractions in Predictive State Representations
Brian Tanner, Vadim Bulitko, Anna Koop, Cosmin Pad...