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cover of episode “A dataset of questions on decision-theoretic reasoning in Newcomb-like problems” by Caspar Oesterheld, Ethan Perez, Chi Nguyen

“A dataset of questions on decision-theoretic reasoning in Newcomb-like problems” by Caspar Oesterheld, Ethan Perez, Chi Nguyen

2024/12/17
logo of podcast LessWrong (30+ Karma)

LessWrong (30+ Karma)

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This is a link post.I’ve spent a lot of the last few years working on issues related to acausal cooperation. With LLMs being clearly dominant over recent years, I’ve now led a team to make a benchmark to figure out how good LLMs are at decision theory and whether and when they lean more CDT or EDT. We hope to expand this dataset in the future, including by incorporating questions that try to measure the updatelessness dimension. Hopefully, this dataset will be useful for future interventions aimed at improving acausal interactions. Abstract: We introduce a dataset of natural-language questions in the decision theory of so-called Newcomb-like problems. Newcomb-like problems include, for instance, decision problems in which an agent interacts with a similar other agent, and thus has to reason about the fact that the other agent will likely reason in similar ways. Evaluating LLM reasoning about Newcomb-like problems is [...]

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First published: December 16th, 2024

Source: https://www.lesswrong.com/posts/d9amcRzns5pwg9Fcu/a-dataset-of-questions-on-decision-theoretic-reasoning-in)

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