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RECOMB
2004
Springer
16 years 2 days ago
Learning Regulatory Network Models that Represent Regulator States and Roles
Abstract. We present an approach to inferring probabilistic models of generegulatory networks that is intended to provide a more mechanistic representation of transcriptional regul...
Keith Noto, Mark Craven
GECCO
2009
Springer
135views Optimization» more  GECCO 2009»
15 years 6 months ago
Neuroevolutionary reinforcement learning for generalized helicopter control
Helicopter hovering is an important challenge problem in the field of reinforcement learning. This paper considers several neuroevolutionary approaches to discovering robust cont...
Rogier Koppejan, Shimon Whiteson
METMBS
2004
151views Mathematics» more  METMBS 2004»
15 years 1 months ago
Machine Learning Techniques for the Evaluation of External Skeletal Fixation Structures
In this thesis we compare several machine learning techniques for evaluating external skeletal fixation proposals. We experimented in the context of dog bone fractures but the pot...
Ning Suo, Khaled Rasheed, Walter D. Potter, Dennis...
GECCO
2010
Springer
187views Optimization» more  GECCO 2010»
15 years 3 months ago
Evolving agent behavior in multiobjective domains using fitness-based shaping
Multiobjective evolutionary algorithms have long been applied to engineering problems. Lately they have also been used to evolve behaviors for intelligent agents. In such applicat...
Jacob Schrum, Risto Miikkulainen
GECCO
2008
Springer
124views Optimization» more  GECCO 2008»
15 years 26 days ago
Introducing MONEDA: scalable multiobjective optimization with a neural estimation of distribution algorithm
In this paper we explore the model–building issue of multiobjective optimization estimation of distribution algorithms. We argue that model–building has some characteristics t...
Luis Martí, Jesús García, Ant...