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ATAL
2008
Springer
13 years 9 months ago
Approximate predictive state representations
Predictive state representations (PSRs) are models that represent the state of a dynamical system as a set of predictions about future events. The existing work with PSRs focuses ...
Britton Wolfe, Michael R. James, Satinder P. Singh
CDC
2009
IEEE
112views Control Systems» more  CDC 2009»
13 years 8 months ago
Prediction-based observation of nonlinear systems non-affine in the unmeasured states
The presented work addresses the observation problem for a large class of nonlinear systems, including systems which are nonlinear in the unmeasured states. Assuming partial state ...
Yannick Morel, Alexander Leonessa
ATAL
2007
Springer
14 years 1 months ago
Subjective approximate solutions for decentralized POMDPs
A problem of planning for cooperative teams under uncertainty is a crucial one in multiagent systems. Decentralized partially observable Markov decision processes (DECPOMDPs) prov...
Anton Chechetka, Katia P. Sycara
ICML
2004
IEEE
14 years 8 months ago
Learning and discovery of predictive state representations in dynamical systems with reset
Predictive state representations (PSRs) are a recently proposed way of modeling controlled dynamical systems. PSR-based models use predictions of observable outcomes of tests that...
Michael R. James, Satinder P. Singh
ICML
2009
IEEE
14 years 8 months ago
Proto-predictive representation of states with simple recurrent temporal-difference networks
We propose a new neural network architecture, called Simple Recurrent Temporal-Difference Networks (SR-TDNs), that learns to predict future observations in partially observable en...
Takaki Makino