In this paper we explore the use of several types of structural restrictions within algorithms for learning Bayesian networks. These restrictions may codify expert knowledge in a g...
Abstract. In constraint programming there are often many choices regarding the propagation method to be used on the constraints of a problem. However, simple constraint solvers usu...
Physical domains are notoriously hard to model completely and correctly, especially to capture the dynamics of the environment. Moreover, since environments change, it is even mor...
Evolutionary Algorithms (EAs) can be used for designing Particle Swarm Optimization (PSO) algorithms that work, in some cases, considerably better than the human-designed ones. By...
We propose an approach to transformational planning and learning of everyday activity. This approach is targeted at autonomous robots that are to perform complex activities such a...