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AAAI
1998
15 years 8 months ago
Solving Very Large Weakly Coupled Markov Decision Processes
We present a technique for computing approximately optimal solutions to stochastic resource allocation problems modeled as Markov decision processes (MDPs). We exploit two key pro...
Nicolas Meuleau, Milos Hauskrecht, Kee-Eung Kim, L...
AAAI
1997
15 years 8 months ago
Incremental Methods for Computing Bounds in Partially Observable Markov Decision Processes
Partially observable Markov decision processes (POMDPs) allow one to model complex dynamic decision or control problems that include both action outcome uncertainty and imperfect ...
Milos Hauskrecht
AIPS
2009
15 years 8 months ago
Automatic Derivation of Memoryless Policies and Finite-State Controllers Using Classical Planners
Finite-state and memoryless controllers are simple action selection mechanisms widely used in domains such as videogames and mobile robotics. Memoryless controllers stand for func...
Blai Bonet, Héctor Palacios, Hector Geffner
GECCO
2008
Springer
165views Optimization» more  GECCO 2008»
15 years 8 months ago
Dual-population genetic algorithm for nonstationary optimization
In order to solve nonstationary optimization problems efficiently, evolutionary algorithms need sufficient diversity to adapt to environmental changes. The dual-population genetic...
Taejin Park, Ri Choe, Kwang Ryel Ryu
KDD
2010
ACM
244views Data Mining» more  KDD 2010»
15 years 5 months ago
Finding effectors in social networks
Assume a network (V, E) where a subset of the nodes in V are active. We consider the problem of selecting a set of k active nodes that best explain the observed activation state, ...
Theodoros Lappas, Evimaria Terzi, Dimitrios Gunopu...