This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
We introduce and describe a novel network simulation tool called NeSSi (Network Security Simulator). NeSSi incorporates a variety of features relevant to network security distingu...
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
Abstract. Amalgamation is a well-known concept for graph transformations in order to model synchronized parallelism of rules with shared subrules and corresponding transformations....
Earth Science Markup Language (ESML) is efficient and effective in representing scientific data in an XML-based formalism. However, features of the data being represented are no...
L. Ian Lumb, J. I. Lederman, J. R. Freemantle, Kei...