Radiative perturbation theory is a computational technique which can greatly ease the burden of repeated solution of the radiative transfer equation for model atmospheres which di...
Motivated by applications in software verification, we explore automated reasoning about the non-disjoint combination of theories of infinitely many finite structures, where the...
Built on the theories of biological neural network, artificial neural network methods have shown many significant advantages. However, the memory space in an artificial neural chip...
Symmetry-breaking in constraint satisfaction problems (CSPs) is a well-established area of AI research which has recently developed strong interactions with symbolic computation, i...
This paper presents an application of information theory to identify sets of key players in social networks. First, we define two entropy measures that we use to analyze the struct...