Transforming Timed Influence Nets into Time Sliced Bayesian Networks

摘要: Abstract : The paper presents an algorithm for transforming Timed Influence Nets (TIN) into Time Sliced Bayesian Networks (TSBN). advantage of TINs lies in their ability to represent both causal and time-sensitive information a compact integrated manner. They are used help decision maker model the temporal interdependencies among variables system. TIN formalism offers suite analysis tools that can be by user analyze impact alternate courses actions on likely outcomes. An even larger, more robust exists TSBNs. These algorithms also allow analyses not available formalism, e.g., provision incorporating real-time form evidence regarding certain calculating its rest knowledge acquisition process TSBNs, however, is intractable large models. This attempt combine advantages modeling paradigms, TSBN, single providing mapping from TSBN. proposed uses approach building TSBN evaluation. A system analyst, this combined approach, interacts with TIN, results obtained mapped back making transformation completely hidden analyst.