A hybrid neuro-symbolic problem-solving model is presented in which the aim is to forecast parameters of a complex and dynamic environment in an unsupervised way. In situations in ...
ion of Assembler Programs for Symbolic Worst Case Execution Time Analysis Tobias Schuele Tobias.Schuele@informatik.uni-kl.de Klaus Schneider Klaus.Schneider@informatik.uni-kl.de Re...
Symbolic AI systems typically have difficulty reasoning about motion in continuous environments, such as determining whether a cornering car will clear a close obstacle. Bimodal s...
In the universal DNA chip method, target RNAs are mapped onto a set of DNA tags. Parallel hybridization of these tags with an indexed, complementary antitag array then provides an ...
John A. Rose, Russell J. Deaton, Masami Hagiya, Ak...
Rectangular hybrid automatamodel digital control programs of analog plant environments. We study rectangular hybrid automatawhere the plant state evolves continuously in real-numbe...