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JIRS
2008
100views more  JIRS 2008»
15 years 6 months ago
Model-based Predictive Control of Hybrid Systems: A Probabilistic Neural-network Approach to Real-time Control
Abstract This paper proposes an approach for reducing the computational complexity of a model-predictive-control strategy for discrete-time hybrid systems with discrete inputs only...
Bostjan Potocnik, Gasper Music, Igor Skrjanc, Boru...
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ITSSA
2006
182views more  ITSSA 2006»
15 years 6 months ago
Evaluation of a Multi-Agent System for Hospital Patient Scheduling
: The problem of patient scheduling in hospitals is characterized by high uncertainty and dynamics in patient treatments. Additional complexity in the planning and coordination pro...
Anja Zöller, Lars Braubach, Alexander Pokahr,...
JMLR
2008
148views more  JMLR 2008»
15 years 6 months ago
Linear-Time Computation of Similarity Measures for Sequential Data
Efficient and expressive comparison of sequences is an essential procedure for learning with sequential data. In this article we propose a generic framework for computation of sim...
Konrad Rieck, Pavel Laskov
JAIR
2006
101views more  JAIR 2006»
15 years 6 months ago
Resource Allocation Among Agents with MDP-Induced Preferences
Allocating scarce resources among agents to maximize global utility is, in general, computationally challenging. We focus on problems where resources enable agents to execute acti...
Dmitri A. Dolgov, Edmund H. Durfee
JFR
2006
108views more  JFR 2006»
15 years 6 months ago
Learning in a hierarchical control system: 4D/RCS in the DARPA LAGR program
The Defense Applied Research Projects Agency (DARPA) Learning Applied to Ground Vehicles (LAGR) program aims to develop algorithms for autonomous vehicle navigation that learn how...
James S. Albus, Roger Bostelman, Tommy Chang, Tsai...
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