Applications of learning to autonomous agents (simulated or real) have often been restricted to learning a mapping from perceived state of the world to the next action to take. Of...
The multiply sectioned Bayesian network (MSBN) framework is the most studied approach for distributed Bayesian Network inference in an MAS setting. This paper describes a new fram...
Abstract-- We consider the problem of optimal netlist simplification in the presence of constraints. Because constraints restrict the reachable states of a netlist, they may enhanc...
We propose a new graph-based semisupervised learning (SSL) algorithm and demonstrate its application to document categorization. Each document is represented by a vertex within a ...
This paper addresses the problem of improving the representation space in a rule-based intelligent system, through exception-based learning. Such a system generally learns rules c...
Cristina Boicu, Gheorghe Tecuci, Mihai Boicu, Dori...