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NIPS
1996
13 years 8 months ago
Why did TD-Gammon Work?
Although TD-Gammon is one of the major successes in machine learning, it has not led to similar impressive breakthroughs in temporal difference learning for other applications or ...
Jordan B. Pollack, Alan D. Blair
IJCNN
2007
IEEE
14 years 1 months ago
Theta Neuron Networks: Robustness to Noise in Embedded Applications
- In this paper, we train a one-layer Theta Neuron Network (TNN) to perform a Braitenberg obstacle avoidance algorithm on a Khepera robot. The Theta neuron model is more biological...
Sam McKennoch, Preethi Sundaradevan, Linda G. Bush...
ICML
2007
IEEE
14 years 8 months ago
Conditional random fields for multi-agent reinforcement learning
Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of obser...
Xinhua Zhang, Douglas Aberdeen, S. V. N. Vishwanat...
WIOPT
2005
IEEE
14 years 29 days ago
NEURAL: A Self-Organizing Routing Algorithm for Ad Hoc Networks
This paper evaluates a self-organizing routing protocol for Ad Hoc network, called the NEUron Routing ALgorithm (NEURAL). NEURAL has been designed taking into account the learning...
Vicente E. Mujica V, Dorgham Sisalem, Radu Popescu...
ICNC
2005
Springer
14 years 27 days ago
Segmentation of SAR Image Using Mixture Multiscale ARMA Network
Abstract. A mixture multiscale autoregressive moving average (ARMA) network is proposed for unsupervised segmentation of synthetic aperture radar (SAR) image. The network combines ...
Haixia Xu, Tian Zheng, Fan Meng