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AAAI
2000
13 years 9 months ago
Localizing Search in Reinforcement Learning
Reinforcement learning (RL) can be impractical for many high dimensional problems because of the computational cost of doing stochastic search in large state spaces. We propose a ...
Gregory Z. Grudic, Lyle H. Ungar
ICRA
2009
IEEE
106views Robotics» more  ICRA 2009»
14 years 2 months ago
Stochastic strategies for a swarm robotic assembly system
— We present a decentralized, scalable approach to assembling a group of heterogeneous parts into different products using a swarm of robots. While the assembly plans are predete...
Loic Matthey, Spring Berman, Vijay Kumar
GECCO
2010
Springer
249views Optimization» more  GECCO 2010»
13 years 10 months ago
Towards improved dispatching rules for complex shop floor scenarios: a genetic programming approach
Developing dispatching rules for manufacturing systems is a tedious process, which is time- and cost-consuming. Since there is no good general rule for different scenarios and ob...
Torsten Hildebrandt, Jens Heger, Bernd Scholz-Reit...
JUCS
2008
153views more  JUCS 2008»
13 years 8 months ago
Bus Network Optimization with a Time-Dependent Hybrid Algorithm
: This paper describes a new hybrid technique that combines a Greedy Randomized Adaptive Search Procedure (GRASP) and a genetic algorithm with simulation features in order to solve...
Ana C. Olivera, Mariano Frutos, Jessica Andrea Car...
IOR
2008
109views more  IOR 2008»
13 years 8 months ago
Polynomial-Time Algorithms for Stochastic Uncapacitated Lot-Sizing Problems
In 1958, Wagner and Whitin published a seminal paper on the deterministic uncapacitated lot-sizing problem, a fundamental model that is embedded in many practical production plann...
Yongpei Guan, Andrew J. Miller