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» A Nonlinear Predictive State Representation
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IEEEICCI
2009
IEEE
13 years 5 months ago
Learning from an ensemble of Receptive Fields
Abstract-In this paper, we construct a neural-inspired computational model based on the representational capabilities of receptive fields. The proposed model, known as Shape Encodi...
Hanlin Goh, Joo Hwe Lim, Chai Quek
ICRA
2007
IEEE
126views Robotics» more  ICRA 2007»
14 years 1 months ago
Semantic Knowledge-Based Execution Monitoring for Mobile Robots
Abstract— We describe a novel intelligent execution monitoring approach for mobile robots acting in indoor environments such as offices and houses. Traditionally, monitoring exe...
Abdelbaki Bouguerra, Lars Karlsson, Alessandro Saf...
ESANN
2008
13 years 9 months ago
Computationally Efficient Neural Field Dynamics
We propose a modification of the dynamic neural field model of Amari [1], aiming at reducing the simulation effort by employing spaceand frequency representations of the dynamic st...
Alexander Gepperth, Jannik Fritsch, Christian Goer...
IWANN
2001
Springer
14 years 1 days ago
Is Neural Network a Reliable Forecaster on Earth? A MARS Query!
: Long-term rainfall prediction is a challenging task especially in the modern world where we are facing the major environmental problem of global warming. In general, climate and ...
Ajith Abraham, Dan Steinberg
ICML
2007
IEEE
14 years 8 months ago
Learning state-action basis functions for hierarchical MDPs
This paper introduces a new approach to actionvalue function approximation by learning basis functions from a spectral decomposition of the state-action manifold. This paper exten...
Sarah Osentoski, Sridhar Mahadevan