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140
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TSMC
2008
146views more  TSMC 2008»
15 years 4 months ago
Decentralized Learning in Markov Games
Learning Automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms. One of the principal contributions of LA theory is tha...
Peter Vrancx, Katja Verbeeck, Ann Nowé
130
Voted
TSP
2010
14 years 11 months ago
MIMO cognitive radio: a game theoretical approach
Abstract--The concept of cognitive radio (CR) has recently received great attention from the research community as a promising paradigm to achieve efficient use of the frequency re...
Gesualdo Scutari, Daniel Pérez Palomar
220
Voted
ICDE
2007
IEEE
117views Database» more  ICDE 2007»
16 years 6 months ago
Finding Skyline and Top-k Bargaining Solutions
We address skyline and top-k processing in web interaction scenarios. We model the problem space based on game theory principles and present new algorithms and heuristics to reali...
Mohamed A. Soliman, Ihab F. Ilyas, Nick Koudas
108
Voted
EUSFLAT
2007
215views Fuzzy Logic» more  EUSFLAT 2007»
15 years 6 months ago
Two Consensus Protocols Based on an Acceptance Threshold in Group Decision Making
We define two negotiation protocols for Group Decision Making, which main feature is the existence of acceptation thresholds. In order to predict which consensus are expected to ...
Christophe Labreuche
AI
2007
Springer
15 years 4 months ago
If multi-agent learning is the answer, what is the question?
The area of learning in multi-agent systems is today one of the most fertile grounds for interaction between game theory and artificial intelligence. We focus on the foundational...
Yoav Shoham, Rob Powers, Trond Grenager