Includes index

Part 1. Introducing probabilistic programming. 1. Probabilistic programming in a nutshell -- 2. A quick Figaro tutorial -- 3. Creating a probabilistic programming application -- 4. Probabilistic models and probabilistic programs -- 5. Modeling dependencies with Bayesian and Markov networks -- 6. Using Scale and Figaro collections to build up models -- 7. Object-oriented probabilistic modeling -- 8. Modeling dynamic systems -- 9. The three rules of probabilistic inference -- 10. Factored inference algorithms -- 11. Sampling algorithms -- 12. Solving other inference tasks -- 13. Dynamic reasonin and parameter learning