Perceptrons, Learning from Mistakes, and a Step Towards AI: An Excerpt from The Laws of Thought: The Quest for a Mathematical Theory of the Mind

Tom Griffiths

doi:10.1090/noti3333

May 1, 2026Notices of the American Mathematical Society

Perceptrons, Learning from Mistakes, and a Step Towards AI: An Excerpt from The Laws of Thought: The Quest for a Mathematical Theory of the Mind

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Key Points

To explore how perceptrons leverage experience to modify neuron connections for learning.
Describes the function and structure of perceptrons and their neural circuits.
Analyzes the role of experience in shaping neuron connections.
Demonstrates that perceptrons can adapt their connections based on learned experiences.
Highlights the implications of this learning process for developing artificial intelligence.

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Implication

This excerpt reveals how perceptrons learn to connect neurons from experience, indicating advancements in AI.

Abstract

What was special about the perceptron was that it didn’t just consist of circuits that were built out of neurons. It used experience to learn how those neurons should be connected to one another.

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Tom Griffiths (2026) studied this question.

synapsesocial.com/papers/6a22686b763171746d546fa9 https://doi.org/10.1090/noti3333

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Perceptrons, Learning from Mistakes, and a Step Towards AI: An Excerpt from The Laws of Thought: The Quest for a Mathematical Theory of the Mind

Key Points

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

Perceptrons, Learning from Mistakes, and a Step Towards AI: An Excerpt from The Laws of Thought: The Quest for a Mathematical Theory of the Mind

Key Points

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

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