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AUSAI
2005
Springer
15 years 6 months ago
Global Versus Local Constructive Function Approximation for On-Line Reinforcement Learning
: In order to scale to problems with large or continuous state-spaces, reinforcement learning algorithms need to be combined with function approximation techniques. The majority of...
Peter Vamplew, Robert Ollington
109
Voted
KDD
2009
ACM
191views Data Mining» more  KDD 2009»
16 years 28 days ago
Scalable pseudo-likelihood estimation in hybrid random fields
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
Antonino Freno, Edmondo Trentin, Marco Gori
82
Voted
RAS
2006
97views more  RAS 2006»
15 years 9 days ago
Visuo-motor learning for face-to-face pass between heterogeneous humanoids
Humanoid behavior generation is one of the most formidable issues due to its complicated structure with many degrees of freedom. This paper proposes a controller for a humanoid to...
Masaki Ogino, Masaaki Kikuchi, Minoru Asada
97
Voted
GECCO
2008
Springer
115views Optimization» more  GECCO 2008»
15 years 1 months ago
A genetic programming approach to business process mining
The aim of process mining is to identify and extract process patterns from data logs to reconstruct an overall process flowchart. As business processes become more and more comple...
Chris J. Turner, Ashutosh Tiwari, Jörn Mehnen
IEEEPACT
1998
IEEE
15 years 4 months ago
Athapascan-1: On-Line Building Data Flow Graph in a Parallel Language
In order to achieve practical efficient execution on a parallel architecture, a knowledge of the data dependencies related to the application appears as the key point for building...
François Galilée, Jean-Louis Roch, G...