Adaptive social learning is a useful tool for studying distributed decision-making problems over graphs. This paper investigates the effect of combination policies on performance adaptive strategies. Using large-deviation analysis, it first derives bound steady-state error probability and characterizes optimal selection Perron eigenvectors policies. It subsequently studies policy transient beha...

We consider the (1+λ) evolution strategy, an evolutionary algorithm for minimization in Rn, using isotropic mutations. Thus, for instance, Gaussian mutations adapted by the 1/5-rule or by σ-self-adaptation are covered. Lower bounds on the (expected) runtime (defined as the number of function evaluations) to overcome a gap in the search space are proved (where the search faces a gap of size ∆ if...

Can we use the constructed predictive model as a basis for action-selection? We develop an event-based anticipation framework for performing latent learning and we provide two mathematical tools to identify relevant relationships between events. These tools allow us to build a predictive model which is then embedded in an action-selection architecture to generate adaptive behavior. We first ana...

In PC clusters or high performance I/O networks including InfiniBand, network topologies often become irregular. Although various adaptive routings for irregular networks have been proposed, most of such commercial or experimental networks use a deterministic routing which enables a simple switch structure and in-order packet delivery. A strategy of path selection algorithm which fixes a single...

airplane in presence of asymmetric left-wing damaged. ‎Variations of the aerodynamic parameters, mass and ‎moments of inertia, and the center of gravity due to ‎damage are all considered in the nonlinear ‎mathematical modeling. The proposed discrete-time ‎nonlinear MRAC algorithm applies the recursive least ‎square (RLS) algorithm as a parameter estimator as ‎well as the error between the real ...

  Supplier selection is one of the critical activities for firms to gain competitive advantage and achieve the objectives of the whole supply chain. In this paper based on a DEA-TOPSIS method for MADM problems a flexible strategy for supplier selection is introduced