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AGENTS
1999
Springer
13 years 9 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»
13 years 10 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
13 years 5 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
13 years 5 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»
13 years 6 months 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