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» Distributed Algorithms and Causally Consistent Observations
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IPPS
2007
IEEE
14 years 1 months ago
Online Aggregation over Trees
Consider a distributed network with nodes arranged in a tree, and each node having a local value. We consider the problem of aggregating values (e.g., summing values) from all nod...
C. Greg Plaxton, Mitul Tiwari, Praveen Yalagandula
JMLR
2008
94views more  JMLR 2008»
13 years 7 months ago
Using Markov Blankets for Causal Structure Learning
We show how a generic feature selection algorithm returning strongly relevant variables can be turned into a causal structure learning algorithm. We prove this under the Faithfuln...
Jean-Philippe Pellet, André Elisseeff
CDC
2009
IEEE
132views Control Systems» more  CDC 2009»
14 years 11 days ago
Q-learning and Pontryagin's Minimum Principle
Abstract— Q-learning is a technique used to compute an optimal policy for a controlled Markov chain based on observations of the system controlled using a non-optimal policy. It ...
Prashant G. Mehta, Sean P. Meyn
INFFUS
2010
143views more  INFFUS 2010»
13 years 6 months ago
A multi-agent systems approach to distributed bayesian information fusion
This paper introduces design principles for modular Bayesian fusion systems which can (i) cope with large quantities of heterogeneous information and (ii) can adapt to changing co...
Gregor Pavlin, Patrick de Oude, Marinus Maris, Jan...
ATAL
2005
Springer
14 years 1 months ago
Tunably decentralized algorithms for cooperative target observation
Multi-agent problem domains may require distributed algorithms for a variety of reasons: local sensors, limitations of communication, and availability of distributed computational...
Sean Luke, Keith Sullivan, Liviu Panait, Gabriel C...