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GECCO
2006
Springer
132views Optimization» more  GECCO 2006»
15 years 7 months ago
Combining genetic algorithms with squeaky-wheel optimization
The AI optimization algorithm called "Squeaky-Wheel Optimization" (SWO) has proven very effective in a variety of real-world applications. Although the ideas behind SWO ...
Justin Terada, Hoa Vo, David Joslin
IJCAI
2001
15 years 5 months ago
R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
Ronen I. Brafman, Moshe Tennenholtz
INFOCOM
2000
IEEE
15 years 8 months ago
Comparisons of Packet Scheduling Algorithms for Fair Service Among Connections on the Internet
Abstract—We investigate the performance of TCP under three representatives of packet scheduling algorithms at the router. Our main focus is to investigate how fair service can be...
Go Hasegawa, Takahiro Matsuo, Masayuki Murata, Hid...
ICWN
2008
15 years 5 months ago
An Access Point Selection Algorithm for Heterogeneous Stations
In wireless LAN technology, access point selection at each station is a critical problem in order to obtain satisfactory throughputs. The current protocol for access point selecti...
Yasuhiro Sagara, Akihiro Fujiwara
GECCO
2008
Springer
124views Optimization» more  GECCO 2008»
15 years 5 months ago
Introducing MONEDA: scalable multiobjective optimization with a neural estimation of distribution algorithm
In this paper we explore the model–building issue of multiobjective optimization estimation of distribution algorithms. We argue that model–building has some characteristics t...
Luis Martí, Jesús García, Ant...