We define the problem of inferring a “mixture of Markov chains” based on observing a stream of interleaved outputs from these chains. We show a sharp characterization of the i...
Hidden Markov models assume that observations in time series data stem from some hidden process that can be compactly represented as a Markov chain. We generalize this model by as...
We study syntax-free models for name-passing processes. For interleaving semantics, we identify the indexing structure required of an early labelled transition system to support t...
Many autonomous systems such as mobile robots, UAVs or spacecraft, have limited resource capacities and move in dynamic environments. Performing on-board mission planning and exec...