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ML
1998
ACM
136views Machine Learning» more  ML 1998»
13 years 9 months ago
Co-Evolution in the Successful Learning of Backgammon Strategy
Following Tesauro’s work on TD-Gammon, we used a 4000 parameter feed-forward neural network to develop a competitive backgammon evaluation function. Play proceeds by a roll of t...
Jordan B. Pollack, Alan D. Blair
FOIKS
2008
Springer
13 years 11 months ago
Cost-Minimising Strategies for Data Labelling: Optimal Stopping and Active Learning
Supervised learning deals with the inference of a distribution over an output or label space Y conditioned on points in an observation space X , given a training dataset D of pair...
Christos Dimitrakakis, Christian Savu-Krohn
SOPR
2008
60views more  SOPR 2008»
13 years 9 months ago
Human resources based improvement strategies - the learning factor
: Processes usually are defined according to underlying standards (ISO 15504, ESA ECSS, ISO 9001, ...) and are described with process steps to be performed by roles and producing r...
Richard Messnarz, Damjan Ekert, Michael Reiner, Ge...
SAGA
2009
Springer
14 years 4 months ago
Bounds for Multistage Stochastic Programs Using Supervised Learning Strategies
We propose a generic method for obtaining quickly good upper bounds on the minimal value of a multistage stochastic program. The method is based on the simulation of a feasible dec...
Boris Defourny, Damien Ernst, Louis Wehenkel
CIG
2005
IEEE
14 years 3 months ago
Coevolution in Hierarchical AI for Strategy Games
Real-Time Strategy games present an interesting problem domain for Artificial Intelligence research. We review current approaches to developing AI systems for such games, noting th...
Daniel Livingstone