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PPSN
2004
Springer
15 years 10 months ago
A Neuroevolutionary Approach to Emergent Task Decomposition
A scalable architecture to facilitate emergent (self-organized) task decomposition using neural networks and evolutionary algorithms is presented. Various control system architectu...
Jekanthan Thangavelautham, Gabriele M. T. D'Eleute...
GECCO
2009
Springer
135views Optimization» more  GECCO 2009»
15 years 12 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
IJCNN
2006
IEEE
15 years 11 months ago
Reinforcement Learning for Parameterized Motor Primitives
Abstract— One of the major challenges in both action generation for robotics and in the understanding of human motor control is to learn the “building blocks of movement genera...
Jan Peters, Stefan Schaal
GECCO
2009
Springer
124views Optimization» more  GECCO 2009»
15 years 10 months ago
Reinforcement learning for games: failures and successes
We apply CMA-ES, an evolution strategy with covariance matrix adaptation, and TDL (Temporal Difference Learning) to reinforcement learning tasks. In both cases these algorithms se...
Wolfgang Konen, Thomas Bartz-Beielstein
BIOSYSTEMS
2007
123views more  BIOSYSTEMS 2007»
15 years 5 months ago
Real time computation: Zooming in on population codes
Information processing in nervous systems intricately combines computation at the neuronal and network levels. Many computations may be envisioned as sequences of signal processin...
Olivier Rochel, Netta Cohen