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What are the methods of inference in automated reasoning? 


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Automated reasoning utilizes various methods of inference. One approach is the symbolic/logic approach, which aims to replicate human reasoning mechanisms. This approach combines deduction, abduction, abstraction, induction, argumentation, uncertainty, and analogy . Another method is structured factored inference (SFI), which decomposes a model into sub-models and applies inference algorithms to each sub-model before combining the results . Fuzzy-based automated reasoning is another technique that uses defuzzification methods to reason about brake-force in vehicle control systems . Additionally, there are shared building blocks between the prime calculi for propositional and first-order logic with equality, such as conflict driven clause learning (CDCL) and superposition . Finally, uncertainty plays a role in automated reasoning, similar to its role in human reasoning and inference .

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The paper does not explicitly mention the methods of inference in automated reasoning. The paper discusses the role of uncertainty in human reasoning and suggests that there may be similar roles for uncertainty in automated reasoning.
The paper does not explicitly mention the methods of inference in automated reasoning.
The paper discusses several methods of inference in automated reasoning, including deduction, abduction, abstraction, induction, argumentation, uncertainty, and analogy.
The paper does not explicitly mention the methods of inference in automated reasoning. The paper focuses on introducing a new framework called structured factored inference (SFI) for automated reasoning in probabilistic programming languages.
The paper does not mention the methods of inference in automated reasoning.

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