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ATAL
2007
Springer
15 years 10 months ago
Letting loose a SPIDER on a network of POMDPs: generating quality guaranteed policies
Distributed Partially Observable Markov Decision Problems (Distributed POMDPs) are a popular approach for modeling multi-agent systems acting in uncertain domains. Given the signi...
Pradeep Varakantham, Janusz Marecki, Yuichi Yabu, ...
ATAL
2008
Springer
15 years 6 months ago
Not all agents are equal: scaling up distributed POMDPs for agent networks
Many applications of networks of agents, including mobile sensor networks, unmanned air vehicles, autonomous underwater vehicles, involve 100s of agents acting collaboratively und...
Janusz Marecki, Tapana Gupta, Pradeep Varakantham,...
BMCBI
2005
100views more  BMCBI 2005»
15 years 3 months ago
Evolutionary models for insertions and deletions in a probabilistic modeling framework
Background: Probabilistic models for sequence comparison (such as hidden Markov models and pair hidden Markov models for proteins and mRNAs, or their context-free grammar counterp...
Elena Rivas
STACS
2012
Springer
13 years 11 months ago
Stabilization of Branching Queueing Networks
Queueing networks are gaining attraction for the performance analysis of parallel computer systems. A Jackson network is a set of interconnected servers, where the completion of a...
Tomás Brázdil, Stefan Kiefer
ICML
2001
IEEE
16 years 4 months ago
Continuous-Time Hierarchical Reinforcement Learning
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
Mohammad Ghavamzadeh, Sridhar Mahadevan