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NECO
2007
150views more  NECO 2007»
15 years 3 months ago
Reinforcement Learning, Spike-Time-Dependent Plasticity, and the BCM Rule
Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is ...
Dorit Baras, Ron Meir
PAMI
2007
186views more  PAMI 2007»
15 years 3 months ago
Value-Directed Human Behavior Analysis from Video Using Partially Observable Markov Decision Processes
—This paper presents a method for learning decision theoretic models of human behaviors from video data. Our system learns relationships between the movements of a person, the co...
Jesse Hoey, James J. Little
FSS
2010
147views more  FSS 2010»
15 years 2 months ago
A divide and conquer method for learning large Fuzzy Cognitive Maps
Fuzzy Cognitive Maps (FCMs) are a convenient tool for modeling and simulating dynamic systems. FCMs were applied in a large number of diverse areas and have already gained momentu...
Wojciech Stach, Lukasz A. Kurgan, Witold Pedrycz
ICRA
2010
IEEE
114views Robotics» more  ICRA 2010»
15 years 2 months ago
A general information quality based approach for satisfying sensor constraints in multirobot tasks
— Many architectures have been proposed to solve tightly-coupled multirobot tasks (MT) through coalitions of heterogeneous robots. However, several issues remain unaddressed. As ...
Yu Zhang, Lynne E. Parker
131
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PAMI
2010
205views more  PAMI 2010»
15 years 2 months ago
Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing
In this paper, we address the tasks of detecting, segmenting, parsing, and matching deformable objects. We use a novel probabilistic object model that we call a hierarchical defor...
Long Zhu, Yuanhao Chen, Alan L. Yuille
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