Analysis and conception of systems
Monday January 7, 2019, 10:30AM, Salle 3052
Louis Mandel (IBM Watson) Reactive Probabilistic Programming
Following this approach, we propose to extends a reactive programming language with probabilistic constructs. This new language enables the modeling of probabilistic reactive systems, that is, probabilistic models in constant interaction with their environment. Examples of such systems include time-series prediction, agent-based systems, or infrastructure self-tuning.
To demonstrate this approach, we started from ReactiveML, a reactive extension of OCaml that supports parallel composition of processes, communication through signals, preemption, and suspension. We extend the language with classic probabilistic constructs (sample, factor à la WebPPL) and propose an inference scheme for reactive processes, that are, non-terminating functions.