Developing complex robotic systems endowed with self-conscious abilities and subjective experience is a hard requirement to face at design time. This paper deals with the developme...
Antonio Chella, Massimo Cossentino, Valeria Seidit...
The error-correcting output coding (ECOC) method reduces the multiclass learning problem into a series of binary classifiers. In this paper, we consider the dense ECOC methods, co...
Aijun Zhang, Zhi-Li Wu, Chun Hung Li, Kai-Tai Fang
Abstract. We use a Markov Chain Monte Carlo (MCMC) MML algorithm to learn hybrid Bayesian networks from observational data. Hybrid networks represent local structure, using conditi...
Typical applications of evolutionary optimization in static environments involve the approximation of the extrema of functions. For dynamic environments, the interest is not to lo...
Models and conceptualizations are necessary to understand and design ubiquitous systems that are context–aware not just from a technological point of view. The current technologi...