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ICASSP
2011
IEEE
13 years 27 days ago
Social norm and long-run learning in peer-to-peer networks
We start by formulating the resource sharing in peer-to-peer (P2P) networks as a random-matching gift-giving game, where self-interested peers aim at maximizing their own long-ter...
Yu Zhang, Mihaela van der Schaar
GECCO
2004
Springer
106views Optimization» more  GECCO 2004»
14 years 2 months ago
The Kalman Swarm: A New Approach to Particle Motion in Swarm Optimization
Abstract. Particle Swarm Optimization is gaining momentum as a simple and effective optimization technique. We present a new approach to PSO that significantly reduces the number...
Christopher K. Monson, Kevin D. Seppi
AE
2005
Springer
14 years 2 months ago
Algorithms (X, sigma, eta): Quasi-random Mutations for Evolution Strategies
Randomization is an efficient tool for global optimization. We here define a method which keeps : – the order 0 of evolutionary algorithms (no gradient) ; – the stochastic as...
Anne Auger, Mohamed Jebalia, Olivier Teytaud
WSC
2007
13 years 11 months ago
Stochastic trust region gradient-free method (strong): a new response-surface-based algorithm in simulation optimization
Response Surface Methodology (RSM) is a metamodelbased optimization method. Its strategy is to explore small subregions of the parameter space in succession instead of attempting ...
Kuo-Hao Chang, L. Jeff Hong, Hong Wan
CORR
2010
Springer
134views Education» more  CORR 2010»
13 years 9 months ago
Incremental Sampling-based Algorithms for Optimal Motion Planning
During the last decade, incremental sampling-based motion planning algorithms, such as the Rapidly-exploring Random Trees (RRTs), have been shown to work well in practice and to po...
Sertac Karaman, Emilio Frazzoli