In this paper we study the topic of CBR systems learning from observations in which those observations can be represented as stochastic policies. We describe a general framework wh...
Kellen Gillespie, Justin Karneeb, Stephen Lee-Urba...
Abstract. In this doctoral work we aim at developing a new approach to labelled semantics and equivalences for the Concurrent Constraint Programming (CCP) which will enable a broad...
We propose strategies to efficiently execute a query workload, which consists of multiple related queries submitted against a scientific dataset, on a distributed-memory system in...
The emerging trend of larger number of cores or processors on a single chip in the server, desktop, and mobile notebook platforms necessarily demands larger amount of on-chip last...
Traditional dynamical systems used for motion tracking cannot effectively handle high dimensionality of the motion states and composite dynamics. In this paper, to address both is...