We propose a general mathematical methodology for studying the dynamics of multiagent systems in which complex collective behavior arises out of local interactions between many si...
A neural network model of associative memory is presented which unifies the two historically more relevant enhancements to the basic Little-Hopfield discrete model: the graded resp...
Enrique Carlos Segura Meccia, Roberto P. J. Perazz...
We investigate fully parallel Newton-Krylov-Schwarz (NKS) algorithms for solving the large sparse nonlinear systems of equations arising from the finite element discretization of ...
Executing long-running parallel applications in Opportunistic Grid environments composed of heterogeneous, shared user workstations, is a daunting task. Machines may fail, become ...
We present actorNet, a mobile agent platform for wireless sensor networks (WSNs). WSNs are well-suited to multiagent systems: agent autonomy reduces the need for communication, sa...