Challenges for Improving Imperative Probabilistic Workflows
Understand how to improve imperative probabilistic workflows in C# by learning to lower complex probabilistic constructs to simpler forms. Explore compiler-like techniques to handle recursion, conditional evaluation, and sampling within a discrete distribution context. This lesson helps you implement and optimize probabilistic games and reason about their expected values programmatically.
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In the previous lesson, we gave you several challenges for improving our DSL for imperative probabilistic workflows.
Compiler Writer’s Approach
Let’s solve a few puzzles:
Question One: You are walking down the street when you see a can of gasoline, some matches, a house on fire, a wrench, a fire hose, and a fire hydrant. You consider the house being on fire to be problematic, so what do you do?
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