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» Robotic Control Using Hierarchical Genetic Programming
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IROS
2009
IEEE
143views Robotics» more  IROS 2009»
14 years 2 months ago
Standing balance control using a trajectory library
— This paper presents a standing balance controller. We employ a library of optimal trajectories and the neighboring optimal control method to generate local approximations to th...
Chenggang Liu, Christopher G. Atkeson
GECCO
2009
Springer
148views Optimization» more  GECCO 2009»
13 years 5 months ago
Genetic programming for quantitative stock selection
We provide an overview of using genetic programming (GP) to model stock returns. Our models employ GP terminals (model decision variables) that are financial factors identified by...
Ying L. Becker, Una-May O'Reilly
BMCBI
2007
172views more  BMCBI 2007»
13 years 7 months ago
msBayes: Pipeline for testing comparative phylogeographic histories using hierarchical approximate Bayesian computation
Background: Although testing for simultaneous divergence (vicariance) across different population-pairs that span the same barrier to gene flow is of central importance to evoluti...
Michael J. Hickerson, Eli Stahl, Naoki Takebayashi
ATAL
2003
Springer
14 years 19 days ago
MONAD: a flexible architecture for multi-agent control
Research in multi-agent systems has led to the development of many multi-agent control architectures. However, we believe that there is currently no known optimal structure for mu...
Thuc Vu, Jared Go, Gal A. Kaminka, Manuela M. Velo...
ICML
1998
IEEE
14 years 8 months ago
Genetic Programming and Deductive-Inductive Learning: A Multi-Strategy Approach
Genetic Programming (GP) is a machine learning technique that was not conceived to use domain knowledge for generating new candidate solutions. It has been shown that GP can bene ...
Ricardo Aler, Daniel Borrajo, Pedro Isasi