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106
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CORR
2007
Springer
73views Education» more  CORR 2007»
15 years 24 days ago
Universal Reinforcement Learning
—We consider an agent interacting with an unmodeled environment. At each time, the agent makes an observation, takes an action, and incurs a cost. Its actions can influence futu...
Vivek F. Farias, Ciamac Cyrus Moallemi, Tsachy Wei...
109
Voted
CVIU
2007
114views more  CVIU 2007»
15 years 23 days ago
Robust real-time vision for a personal service robot
We address visual perception for personal service robotic systems in the home. We start by identifying the main functional modules and their relationships. This includes self-loca...
Gérard G. Medioni, Alexandre R. J. Fran&cce...
112
Voted
PRESENCE
2006
197views more  PRESENCE 2006»
15 years 22 days ago
A Spring Model for Whole-Hand Virtual Grasping
We present a physically-based approach to grasping and manipulation of virtual objects that produces visually realistic results, addresses the problem of visual interpenetration o...
Christoph W. Borst, Arun P. Indugula
IJCSS
2007
122views more  IJCSS 2007»
15 years 22 days ago
Artificial Neural Network Type Learning with Single Multiplicative Spiking Neuron
In this paper, learning algorithm for a single multiplicative spiking neuron (MSN) is proposed and tested for various applications where a multilayer perceptron (MLP) neural netwo...
Deepak Mishra, Abhishek Yadav, Sudipta Ray, Prem K...
106
Voted
TCS
2008
15 years 22 days ago
Modeling spiking neural networks
A notation for the functional specification of a wide range of neural networks consisting of temporal or non-temporal neurons, is proposed. The notation is primarily a mathematica...
Ioannis D. Zaharakis, Achilles D. Kameas