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CIA
2006
Springer
15 years 6 months ago
Learning to Negotiate Optimally in Non-stationary Environments
Abstract. We adopt the Markov chain framework to model bilateral negotiations among agents in dynamic environments and use Bayesian learning to enable them to learn an optimal stra...
Vidya Narayanan, Nicholas R. Jennings
NIPS
1993
15 years 3 months ago
Optimal Stochastic Search and Adaptive Momentum
Stochastic optimization algorithms typically use learning rate schedules that behave asymptotically as (t) = 0=t. The ensemble dynamics (Leen and Moody, 1993) for such algorithms ...
Todd K. Leen, Genevieve B. Orr
ANOR
2010
102views more  ANOR 2010»
15 years 2 months ago
Ejection chain and filter-and-fan methods in combinatorial optimization
The design of effective neighborhood structures is fundamentally important for creating better local search and metaheuristic algorithms for combinatorial optimization. Significant...
César Rego, Fred Glover
CEC
2008
IEEE
15 years 8 months ago
Differential evolution particle swarm optimization for digital filter design
— In this paper, swarm and evolutionary algorithms have been applied for the design of digital filters. Particle swarm optimization (PSO) and differential evolution particle swar...
Bipul Luitel, Ganesh K. Venayagamoorthy
CEC
2008
IEEE
15 years 8 months ago
Analysis of reproduction operator in Bacterial Foraging Optimization Algorithm
— One of the major driving forces of Bacterial Foraging Optimization Algorithm (BFOA) is the reproduction phenomenon of virtual bacteria each of which models one trial solution o...
Ajith Abraham, Arijit Biswas, Sambarta Dasgupta, S...