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ATAL
2007
Springer
14 years 3 hour ago
Multiagent reinforcement learning and self-organization in a network of agents
To cope with large scale, agents are usually organized in a network such that an agent interacts only with its immediate neighbors in the network. Reinforcement learning technique...
Sherief Abdallah, Victor R. Lesser
BMCBI
2006
137views more  BMCBI 2006»
13 years 5 months ago
A maximum likelihood framework for protein design
Background: The aim of protein design is to predict amino-acid sequences compatible with a given target structure. Traditionally envisioned as a purely thermodynamic question, thi...
Claudia L. Kleinman, Nicolas Rodrigue, Céci...
CVPR
2009
IEEE
15 years 28 days ago
Harris Corners in the Real World: A Principled Selection Criterion for Interest Points Based on Ecological Statistics
In this report, we consider whether statistical regularities in natural images might be exploited to provide an improved selection criterion for interest points. One approach that ...
Neil D. B. Bruce, Pierre Kornprobst
FLAIRS
1998
13 years 7 months ago
An AI Approach to Computer Assisted Tomography
Computer assisted tomography (CAT) systems demandlarge amounts of time and space. In this paper, wedescribe an approachto solving the CAT problemusing several AItechniques includi...
John F. Kolen, David A. Shamma, Thomas Reichherzer...
SSIAI
2000
IEEE
13 years 10 months ago
A New Bayesian Relaxation Framework for the Estimation and Segmentation of Multiple Motions
In this paper we propose a new probabilistic relaxation framework to perform robust multiple motion estimation and segmentation from a sequence of images. Our approach uses displa...
Alexander Strehl, Jake K. Aggarwal