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108
Voted
CG
2000
Springer
15 years 5 months ago
Chess Neighborhoods, Function Combination, and Reinforcement Learning
Abstract. Over the years, various research projects have attempted to develop a chess program that learns to play well given little prior knowledge beyond the rules of the game. Ea...
Robert Levinson, Ryan Weber
129
Voted
ATAL
2008
Springer
15 years 2 months ago
No-regret learning and a mechanism for distributed multiagent planning
We develop a novel mechanism for coordinated, distributed multiagent planning. We consider problems stated as a collection of single-agent planning problems coupled by common soft...
Jan-P. Calliess, Geoffrey J. Gordon
CORR
2010
Springer
103views Education» more  CORR 2010»
15 years 23 days ago
Spatially-Adaptive Reconstruction in Computed Tomography Based on Statistical Learning
We propose a direct reconstruction algorithm for Computed Tomography, based on a local fusion of a few preliminary image estimates by means of a non-linear fusion rule. One such ru...
Joseph Shtok, Michael Zibulevsky, Michael Elad
ITICSE
2004
ACM
15 years 6 months ago
Teaching computer networking with the help of personal computer networks
This paper describes an “experiential” learning approach to teaching a foundational course on Computer Networking. In additional to the traditional laboratory sessions and ana...
Rocky K. C. Chang
98
Voted
ATAL
2009
Springer
15 years 7 months ago
A self-organizing neural network architecture for intentional planning agents
This paper presents a model of neural network embodiment of intentions and planning mechanisms for autonomous agents. The model bridges the dichotomy of symbolic and non-symbolic ...
Budhitama Subagdja, Ah-Hwee Tan