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- Description:
Bayesian Logic (BLOG) is a probabilistic modeling language. It is designed for representing relations and uncertainties among real world objects. For instance, tracking multiple targets in a video. BLOG makes it easy and concise to represent - uncertainty about the existence (and the number) of underlying objects - uncertain relations among objects - dependencies among relations and functions - observed evidence
BLOG also provides a query language to ask questions about what the world could possibly be after making observations.
BLOG also refers to the default inference system for models specified in BLOG language.
The BLOG system is developed in Java. Any Java function can be easily called within the BLOG system. It also has a Scala interactive shell and a translator for Scala.
- Changes to previous version:
Initial Announcement on mloss.org.
- BibTeX Entry: Download
- Corresponding Paper BibTeX Entry: Download
- Supported Operating Systems: Linux, Windows, Ubuntu, Mac Os
- Data Formats: Various
- Tags: Sampling, Probabilistic Models, Bayesian Inference, Generic Programming
- Archive: download here
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