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AAAI
2006
15 years 1 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
103
Voted
ICML
2008
IEEE
16 years 1 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
115
Voted
ATAL
2010
Springer
15 years 1 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
AAAI
2007
15 years 2 months ago
Abstraction in Predictive State Representations
Vishal Soni, Satinder P. Singh
IJCAI
2007
15 years 1 months ago
Grounding Abstractions in Predictive State Representations
Brian Tanner, Vadim Bulitko, Anna Koop, Cosmin Pad...