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» Formalizing Multi-state Learning Dynamics
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TSMC
2008
229views more  TSMC 2008»
13 years 10 months ago
A Comprehensive Survey of Multiagent Reinforcement Learning
Multiagent systems are rapidly finding applications in a variety of domains, including robotics, distributed control, telecommunications, and economics. The complexity of many task...
Lucian Busoniu, Robert Babuska, Bart De Schutter
ACL
2009
13 years 8 months ago
Unsupervised Multilingual Grammar Induction
We investigate the task of unsupervised constituency parsing from bilingual parallel corpora. Our goal is to use bilingual cues to learn improved parsing models for each language ...
Benjamin Snyder, Tahira Naseem, Regina Barzilay
ATAL
2010
Springer
13 years 11 months ago
Self-organization for coordinating decentralized reinforcement learning
Decentralized reinforcement learning (DRL) has been applied to a number of distributed applications. However, one of the main challenges faced by DRL is its convergence. Previous ...
Chongjie Zhang, Victor R. Lesser, Sherief Abdallah
ATS
2009
IEEE
142views Hardware» more  ATS 2009»
14 years 5 months ago
Speeding up SAT-Based ATPG Using Dynamic Clause Activation
Abstract—SAT-based ATPG turned out to be a robust alternative to classical structural ATPG algorithms such as FAN. The number of unclassified faults can be significantly reduce...
Stephan Eggersglüß, Daniel Tille, Rolf ...
AAAI
1994
13 years 11 months ago
Learning to Coordinate without Sharing Information
Researchers in the eld of Distributed Arti cial Intelligence (DAI) have been developing e cient mechanisms to coordinate the activities of multiple autonomous agents. The need for...
Sandip Sen, Mahendra Sekaran, John Hale