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ATAL
2015
Springer
3 years 1 months ago
Predictive State Representations with State Space Partitioning
Predictive state representations (PSRs) are powerful methods of modeling dynamical systems by representing state through observational data. Most of the current PSR techniques foc...
Yunlong Liu, Yun Tang, Yifeng Zeng
FLAIRS
2008
8 years 7 months ago
State Space Compression with Predictive Representations
Current studies have demonstrated that the representational power of predictive state representations (PSRs) is at least equal to the one of partially observable Markov decision p...
Abdeslam Boularias, Masoumeh T. Izadi, Brahim Chai...
INFORMS
1998
142views more  INFORMS 1998»
8 years 5 months ago
Distributed State Space Generation of Discrete-State Stochastic Models
High-level formalisms such as stochastic Petri nets can be used to model complex systems. Analysis of logical and numerical properties of these models often requires the generatio...
Gianfranco Ciardo, Joshua Gluckman, David M. Nicol
DSRT
2005
IEEE
8 years 11 months ago
Modeling Decentralized Real-Time Control by State Space Partition of Timed Automata
Timed automata provide useful state machine based representations for the validation and veriļ¬cation of realtime control systems. This paper introduces an algorithmic methodolog...
Thanikesavan Sivanthi, Srivas Chennu, Lothar Kreft
FLAIRS
2004
8 years 6 months ago
State Space Reduction For Hierarchical Reinforcement Learning
er provides new techniques for abstracting the state space of a Markov Decision Process (MDP). These techniques extend one of the recent minimization models, known as -reduction, ...
Mehran Asadi, Manfred Huber
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