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AAAI
2011
14 years 1 months ago
An Online Spectral Learning Algorithm for Partially Observable Nonlinear Dynamical Systems
Recently, a number of researchers have proposed spectral algorithms for learning models of dynamical systems—for example, Hidden Markov Models (HMMs), Partially Observable Marko...
Byron Boots, Geoffrey J. Gordon
ATAL
2009
Springer
15 years 8 months ago
Planning with continuous resources for agent teams
Many problems of multiagent planning under uncertainty require distributed reasoning with continuous resources and resource limits. Decentralized Markov Decision Problems (Dec-MDP...
Janusz Marecki, Milind Tambe
ATAL
2006
Springer
15 years 5 months ago
Winning back the CUP for distributed POMDPs: planning over continuous belief spaces
Distributed Partially Observable Markov Decision Problems (Distributed POMDPs) are evolving as a popular approach for modeling multiagent systems, and many different algorithms ha...
Pradeep Varakantham, Ranjit Nair, Milind Tambe, Ma...
ECML
2006
Springer
15 years 3 months ago
Reinforcement Learning for MDPs with Constraints
In this article, I will consider Markov Decision Processes with two criteria, each defined as the expected value of an infinite horizon cumulative return. The second criterion is e...
Peter Geibel
91
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GECCO
2005
Springer
130views Optimization» more  GECCO 2005»
15 years 7 months ago
ATNoSFERES revisited
ATNoSFERES is a Pittsburgh style Learning Classifier System (LCS) in which the rules are represented as edges of an Augmented Transition Network. Genotypes are strings of tokens ...
Samuel Landau, Olivier Sigaud, Marc Schoenauer