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AGENTS
1999
Springer
15 years 3 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
HICSS
2003
IEEE
207views Biometrics» more  HICSS 2003»
15 years 4 months ago
Formalizing Multi-Agent POMDP's in the context of network routing
This paper uses partially observable Markov decision processes (POMDP’s) as a basic framework for MultiAgent planning. We distinguish three perspectives: first one is that of a...
Bharaneedharan Rathnasabapathy, Piotr J. Gmytrasie...
FOCS
2008
IEEE
14 years 11 months ago
Market Equilibria in Polynomial Time for Fixed Number of Goods or Agents
We consider markets in the classical Arrow-Debreu model. There are n agents and m goods. Each buyer has a concave utility function (of the bundle of goods he/she buys) and an init...
Nikhil R. Devanur, Ravi Kannan
CEC
2010
IEEE
14 years 11 months ago
Cooperative Co-evolution with delta grouping for large scale non-separable function optimization
— Many evolutionary algorithms have been proposed for large scale optimization. Parameter interaction in nonseparable problems is a major source of performance loss specially on ...
Mohammad Nabi Omidvar, Xiaodong Li, Xin Yao
GECCO
2008
Springer
120views Optimization» more  GECCO 2008»
15 years 20 days ago
A robust evolutionary framework for multi-objective optimization
Evolutionary multi-objective optimization (EMO) methodologies, suggested in the beginning of Nineties, focussed on the task of finding a set of well-converged and well-distribute...
Kalyanmoy Deb