Diagnosability of systems is an essential property that determines how accurate any diagnostic reasoning can be on a system given any sequence of observations. Generally, in the l...
This work shows asymptotic convergence to global optima for a family of dynamically scaled genetic programming systems where the underlying population consists of a fixed number o...
Many multi-agent systems consist of a complex network of autonomous yet interdependent agents. Examples of such networked multi-agent systems include supply chains and sensor netw...
We present a Bayesian clustering algorithm for multivariate time series. A clustering is regarded as a probabilistic model in which the unknown auto-correlation structure of a tim...
We study an evolutionary algorithm used for optimizing in a chaotically changing dynamic environment. The corresponding chaotic non–stationary fitness landscape can be character...