Multi-agent system research is concerned with the issues surrounding the performance of collections of interacting agents. A major concern, therefore, is with the design of the dec...
Probabilistic (or randomized) decision trees can be used to compute Boolean functions. We consider two types of probabilistic decision trees - one has a certain probability to give...
Laura Mancinska, Maris Ozols, Ilze Dzelme-Berzina,...
We study the convergence of Markov Decision Processes made of a large number of objects to optimization problems on ordinary differential equations (ODE). We show that the optimal...
—Becoming more competitive and more effective in the current scenes of Business and Public Administration, the organizations must be able to approach easily and quickly to the in...
Marcello Castellano, Giuseppe Mastronardi, Angela ...
The majority of the existing algorithms for learning decision trees are greedy--a tree is induced top-down, making locally optimal decisions at each node. In most cases, however, ...