Planning under uncertainty is an important and challenging problem in multiagent systems. Multiagent Partially Observable Markov Decision Processes (MPOMDPs) provide a powerful fr...
We consider the problem of constructing decision trees for entity identification from a given table. The input is a table containing information about a set of entities over a fi...
Venkatesan T. Chakaravarthy, Vinayaka Pandit, Samb...
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,...
In this paper we shall represent strategic planning problems by dynamic decision trees, in which the nodes are projects that can be deferred or postponed for a certain period of t...
Classification problems with functionally structured input variables arise naturally in many applications. In a clinical domain, for example, input variables could include a time...