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GECCO
2009
Springer
130views Optimization» more  GECCO 2009»
15 years 11 months ago
Neutrality and variability: two sides of evolvability in linear genetic programming
The notion of evolvability has been put forward to describe the“core mechanism”of natural and artificial evolution. Recently, studies have revealed the influence of the envi...
Ting Hu, Wolfgang Banzhaf
ICALP
2010
Springer
15 years 8 months ago
Covering and Packing in Linear Space
Abstract. Given a family of subsets of an n-element universe, the kcover problem asks whether there are k sets in the family whose union contains the universe; in the k-packing pro...
Andreas Björklund, Thore Husfeldt, Petteri Ka...
IJCAI
2007
15 years 8 months ago
Using Linear Programming for Bayesian Exploration in Markov Decision Processes
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
Pablo Samuel Castro, Doina Precup
NIPS
2004
15 years 8 months ago
Worst-Case Analysis of Selective Sampling for Linear-Threshold Algorithms
We provide a worst-case analysis of selective sampling algorithms for learning linear threshold functions. The algorithms considered in this paper are Perceptron-like algorithms, ...
Nicolò Cesa-Bianchi, Claudio Gentile, Luca ...
HIS
2003
15 years 8 months ago
Rated MCRDR: Finding non-Linear Relationships Between Classifications in MCRDR
Multiple Classification Ripple Down Rules (MCRDR) is a simple and effective knowledge acquisition technique that produces representations, or knowledge maps, of a human expert’s ...
Richard Dazeley, Byeong Ho Kang