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GECCO
2003
Springer
117views Optimization» more  GECCO 2003»
15 years 12 months ago
A Method for Handling Numerical Attributes in GA-Based Inductive Concept Learners
This paper proposes a method for dealing with numerical attributes in inductive concept learning systems based on genetic algorithms. The method uses constraints for restricting th...
Federico Divina, Maarten Keijzer, Elena Marchiori
NIPS
2007
15 years 8 months ago
Optimistic Linear Programming gives Logarithmic Regret for Irreducible MDPs
We present an algorithm called Optimistic Linear Programming (OLP) for learning to optimize average reward in an irreducible but otherwise unknown Markov decision process (MDP). O...
Ambuj Tewari, Peter L. Bartlett
AUTOMATICA
2008
134views more  AUTOMATICA 2008»
15 years 6 months ago
Probabilistic reachability and safety for controlled discrete time stochastic hybrid systems
In this work, probabilistic reachability over a finite horizon is investigated for a class of discrete time stochastic hybrid systems with control inputs. A suitable embedding of ...
Alessandro Abate, Maria Prandini, John Lygeros, Sh...
WWW
2011
ACM
15 years 1 months ago
Survivability-oriented self-tuning of web systems
Running in a highly uncertain and changing environment, Web systems cannot always provide full set of services with optimal quality, especially when the workload is high or failur...
Bihuan Chen, Xin Peng, Yijun Yu, Wenyun Zhao
GECCO
2007
Springer
195views Optimization» more  GECCO 2007»
16 years 23 days ago
MILCS: a mutual information learning classifier system
This paper introduces a new variety of learning classifier system (LCS), called MILCS, which utilizes mutual information as fitness feedback. Unlike most LCSs, MILCS is specifical...
Robert Elliott Smith, Max Kun Jiang