Training neural nets with the reactive tabu search

Training neural nets with the reactive tabu search

In this paper the task of training subsymbolic systems is considered as a combinatorial optimization problem and solved with the heuristic scheme of the reactive tabu search (RTS). An iterative optimization process based on a "modified local search" component is complemented with a meta-strategy to realize a discrete dynamical system that discourages limit cycles and the confinement of the sear...

Battiti and Tecchiolli : Training Neural Nets with the Reactive Tabu

| In this paper the task of training sub-symbolic systems is considered as a combinatorial optimization problem and solved with the heuristic scheme of the Reactive Tabu Search. An iterative optimization process based on a \modiied greedy search" component is complemented with a meta-strategy to realize a discrete dynamical system that discourages limit cycles and the connnement of the search t...

The Reactive Tabu Search

We propose an algorithm for combinatorial optimization where an explicit check for the repetition of configurations is added to the basic scheme of Tabu search. In our Tabu scheme the appropriate size of the list is learned in an automated way by reacting to the occurrence of cycles. In addition, if the search appears to be repeating an excessive number of solutions excessively often, then the ...

Vector Quantization with the Reactive Tabu Search

The continuous reactive tabu search :

A novel algorithm for the global optimization of functions (C-RTS) is presented, in which a combinato-rial optimization method cooperates with a stochastic local minimizer. The combinatorial optimization component, based on the Reactive Tabu Search recently proposed by the authors, locates the most promising \boxes," where starting points for the local minimizer are generated. In order to cover...