Logical Reasoning
Summary
Logical Reasoning, as explored in the field of AI alignment research, focuses on developing computable algorithms that can assign and refine probabilities to logical statements within a formal language. The concept of logical induction, as presented in the abstract, introduces a novel approach to addressing the problem of logical non-omniscience in artificial reasoning systems. This approach draws parallels between logical reasoning and stock trading, where logical sentences are treated as stocks with values dependent on their truth. The logical induction criterion aims to create a market-like system where a reasoner’s beliefs are represented as market prices, and the reasoner is considered a logical inductor if no polynomial-time computable trading strategy can consistently outperform it. This framework offers several advantages, including the ability to surpass underlying deductive processes, perform universal empirical induction given sufficient time, and exhibit strong self-trust in the reasoning process, all of which are crucial aspects in developing more robust and aligned AI systems.