NCAIOct 28, 2012

Illustrating a neural model of logic computations: The case of Sherlock Holmes' old maxim

arXiv:1210.7495v3
Originality Synthesis-oriented
AI Analysis

This addresses a cognitive problem for understanding human reasoning, but it is incremental as it builds on existing theories of neural logic.

The paper investigates why humans intuitively accept Sherlock Holmes' maxim as true, proposing that adult brains have neural modules performing modal logical computations.

Natural languages can express some logical propositions that humans are able to understand. We illustrate this fact with a famous text that Conan Doyle attributed to Holmes: 'It is an old maxim of mine that when you have excluded the impossible, whatever remains, however improbable, must be the truth'. This is a subtle logical statement usually felt as an evident truth. The problem we are trying to solve is the cognitive reason for such a feeling. We postulate here that we accept Holmes' maxim as true because our adult brains are equipped with neural modules that naturally perform modal logical computations.

Foundations

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