Foundations of Probability Theory for AI - The Application of Algorithmic Probability to Problems in Artificial Intelligence

📝 Original Info

• Title: Foundations of Probability Theory for AI - The Application of Algorithmic Probability to Problems in Artificial Intelligence
• ArXiv ID: 1304.3424
• Date: 2013-04-15
• Authors: Researchers from original ArXiv paper

📝 Abstract

This paper covers two topics: first an introduction to Algorithmic Complexity Theory: how it defines probability, some of its characteristic properties and past successful applications. Second, we apply it to problems in A.I. - where it promises to give near optimum search procedures for two very broad classes of problems.

💡 Deep Analysis

Deep Dive into Foundations of Probability Theory for AI - The Application of Algorithmic Probability to Problems in Artificial Intelligence.

This paper covers two topics: first an introduction to Algorithmic Complexity Theory: how it defines probability, some of its characteristic properties and past successful applications. Second, we apply it to problems in A.I. - where it promises to give near optimum search procedures for two very broad classes of problems.

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