Temporal Properties of Conditional Independence in Dynamic Bayesian Networks
Aus International Center for Computational Logic
Temporal Properties of Conditional Independence in Dynamic Bayesian Networks
Vortrag von Rajab Aghamov
- Veranstaltungsort: APB 3027
- Beginn: 28. Januar 2027 um 11:00
- Ende: 28. Januar 2027 um 12:00
- Forschungsgruppe: Wissensbasierte Systeme
- Event series: Research Seminar Logic and AI
- iCal
Dynamic Bayesian networks (DBNs) provide compact graphical representations of probabilistic systems that evolve over time. This talk presents results on verifying the evolution of conditional-independence propositions against temporal specifications. Two interpretations are considered: stochastic conditional independence, which takes the concrete probability distributions into account, and structural conditional independence, which depends only on the graphical structure. Deciding whether a stochastic conditional-independence proposition eventually holds is shown to be Skolem-hard. For structural conditional independence, verification against linear temporal logic (LTL) specifications and NBA is in PSPACE and is both NP-hard and coNP-hard.
