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GECCO
2005
Springer
162views Optimization» more  GECCO 2005»
16 years 4 days ago
An autonomous explore/exploit strategy
In reinforcement learning problems it has been considered that neither exploitation nor exploration can be pursued exclusively without failing at the task. The optimal balance bet...
Alex McMahon, Dan Scott, William N. L. Browne
ECML
2006
Springer
15 years 10 months ago
An Adaptive Kernel Method for Semi-supervised Clustering
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...
Bojun Yan, Carlotta Domeniconi
GECCO
2006
Springer
142views Optimization» more  GECCO 2006»
15 years 10 months ago
Classifier prediction based on tile coding
This paper introduces XCSF extended with tile coding prediction: each classifier implements a tile coding approximator; the genetic algorithm is used to adapt both classifier cond...
Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wils...
GECCO
2006
Springer
186views Optimization» more  GECCO 2006»
15 years 10 months ago
Genetic algorithms for action set selection across domains: a demonstration
Action set selection in Markov Decision Processes (MDPs) is an area of research that has received little attention. On the other hand, the set of actions available to an MDP agent...
Greg Lee, Vadim Bulitko
175
Voted
EWRL
2008
15 years 8 months ago
Optimistic Planning of Deterministic Systems
If one possesses a model of a controlled deterministic system, then from any state, one may consider the set of all possible reachable states starting from that state and using any...
Jean-François Hren, Rémi Munos