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AGENTS
1999
Springer
15 years 2 months ago
General Principles of Learning-Based Multi-Agent Systems
We consider the problem of how to design large decentralized multiagent systems (MAS’s) in an automated fashion, with little or no hand-tuning. Our approach has each agent run a...
David Wolpert, Kevin R. Wheeler, Kagan Tumer
INCDM
2010
Springer
146views Data Mining» more  INCDM 2010»
15 years 2 months ago
Learning from Humanoid Cartoon Designs
Abstract. Character design is a key ingredient to the success of any comicbook, graphic novel, or animated feature. Artists typically use shape, size and proportion as the first de...
Md. Tanvirul Islam, Kaiser Md. Nahiduzzaman, Why Y...
AIIA
2003
Springer
15 years 3 months ago
Improving the SLA Algorithm Using Association Rules
A bayesian network is an appropriate tool for working with uncertainty and probability, that are typical of real-life applications. In literature we find different approaches for b...
Evelina Lamma, Fabrizio Riguzzi, Andrea Stambazzi,...
AAAI
2011
13 years 10 months ago
Mean Field Inference in Dependency Networks: An Empirical Study
Dependency networks are a compelling alternative to Bayesian networks for learning joint probability distributions from data and using them to compute probabilities. A dependency ...
Daniel Lowd, Arash Shamaei
ISMIS
2005
Springer
15 years 3 months ago
Learning the Daily Model of Network Traffic
Abstract. Anomaly detection is based on profiles that represent normal behaviour of users, hosts or networks and detects attacks as significant deviations from these profiles. In t...
Costantina Caruso, Donato Malerba, Davide Papagni