Evaluation of Uncertain Inference Models I: PROSPECTOR

📝 Original Info

• Title: Evaluation of Uncertain Inference Models I: PROSPECTOR
• ArXiv ID: 1304.3117
• Date: 2013-04-12
• Authors: Researchers from original ArXiv paper

📝 Abstract

This paper examines the accuracy of the PROSPECTOR model for uncertain reasoning. PROSPECTOR's solutions for a large number of computer-generated inference networks were compared to those obtained from probability theory and minimum cross-entropy calculations. PROSPECTOR's answers were generally accurate for a restricted subset of problems that are consistent with its assumptions. However, even within this subset, we identified conditions under which PROSPECTOR's performance deteriorates.

💡 Deep Analysis

Deep Dive into Evaluation of Uncertain Inference Models I: PROSPECTOR.

This paper examines the accuracy of the PROSPECTOR model for uncertain reasoning. PROSPECTOR’s solutions for a large number of computer-generated inference networks were compared to those obtained from probability theory and minimum cross-entropy calculations. PROSPECTOR’s answers were generally accurate for a restricted subset of problems that are consistent with its assumptions. However, even within this subset, we identified conditions under which PROSPECTOR’s performance deteriorates.

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