HyperNEAT represents a class of neuroevolutionary algorithms that captures some of the power of natural development with a ionally efficient high-level abstraction of development....
Jeff Clune, Benjamin E. Beckmann, Philip K. McKinl...
One has a large workload that is “divisible” (its constituent work’s granularity can be adjusted arbitrarily) and one has access to p remote computers that can assist in comp...
Anne Benoit, Yves Robert, Arnold L. Rosenberg, Fr&...
The design of feature spaces for local image descriptors is an important research subject in computer vision due to its applicability in several problems, such as visual classifi...
Matching problems in Description Logics are theoretically well understood, with a variety of algorithms available for different DLs. Nevertheless, still no implementation of a ge...
Recent work has demonstrated that treating resource reasoning separately from causal reasoning can lead to improved planning performance and rational resource management where inc...