Decision-theoretic models have become increasingly popular as a basis for solving agent and multiagent problems, due to their ability to quantify the complex uncertainty and prefe...
Abstract. Due to the complexity and uncertainties, the engineering process requires dynamic collaborations among the heterogeneous systems and human interactions. In this paper, we...
Jian Cao, Jie Wang, Shen-sheng Zhang, Minglu Li, K...
Building genetic regulatory networks from time series data of gene expression patterns is an important topic in bioinformatics. Probabilistic Boolean networks (PBNs) have been deve...
—This research aims to enable robots to learn from human teachers. Motivated by human social learning, we believe that a transparent learning process can help guide the human tea...
Based on the coherence principle of de Finetti and a related notion of generalized coherence (g-coherence), we adopt a probabilistic approach to uncertainty based on conditional p...
Veronica Biazzo, Angelo Gilio, Giuseppe Sanfilippo