We present a new probabilistic framework for finding likely variable assignments in difficult constraint satisfaction problems. Finding such assignments is key to efficient sea...
Eric I. Hsu, Matthew Kitching, Fahiem Bacchus, She...
In environments which possess relatively few features that enable a robot to unambiguously determine its location, global localization algorithms can result in multiple hypotheses...
Shivudu Bhuvanagiri, K. Madhava Krishna, Supreeth ...
In modern business, educational, and other settings, it is common to provide a digital network that interconnects hardware devices for shared access by the users (e.g., in an of...
Schema learning is a way to discover probabilistic, constructivist, predictive action models (schemas) from experience. It includes methods for finding and using hidden state to m...
— The computation of periodic orbits of nonlinear mappings is very important for studying and better understanding the dynamics of complex systems. Evolutionary algorithms have s...
Y. G. Petalas, Konstantinos E. Parsopoulos, Michae...