NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
Intelligent machines in the twenty-first century: foundations of inference and inquiryThe last century saw the application of Boolean algebra to the construction of computing machines, which work by applying logical transformations to information contained in their memory. The development of information theory and the generalization of Boolean algebra to Bayesian inference have enabled these computing machines, in the last quarter of the twentieth century, to be endowed with the ability to learn by making inferences from data. This revolution is just beginning as new computational techniques continue to make difficult problems more accessible. Recent advances in our understanding of the foundations of probability theory have revealed implications for areas other than logic. Of relevance to intelligent machines, we recently identified the algebra of questions as the free distributive algebra, which will now allow us to work with questions in a way analogous to that which Boolean algebra enables us to work with logical statements. In this paper, we examine the foundations of inference and inquiry. We begin with a history of inferential reasoning, highlighting key concepts that have led to the automation of inference in modern machine-learning systems. We then discuss the foundations of inference in more detail using a modern viewpoint that relies on the mathematics of partially ordered sets and the scaffolding of lattice theory. This new viewpoint allows us to develop the logic of inquiry and introduce a measure describing the relevance of a proposed question to an unresolved issue. Last, we will demonstrate the automation of inference, and discuss how this new logic of inquiry will enable intelligent machines to ask questions. Automation of both inference and inquiry promises to allow robots to perform science in the far reaches of our solar system and in other star systems by enabling them not only to make inferences from data, but also to decide which question to ask, which experiment to perform, or which measurement to take given what they have learned and what they are designed to understand.
Document ID
20040087443
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Knuth, Kevin H.
(NASA Ames Research Center Moffett Field CA United States)
Date Acquired
August 21, 2013
Publication Date
December 15, 2003
Publication Information
Publication: Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Volume: 361
Issue: 1813
ISSN: 1364-503X
Subject Category
Cybernetics, Artificial Intelligence And Robotics
Distribution Limits
Public
Copyright
Other
Keywords
Review
Review, Tutorial

Available Downloads

There are no available downloads for this record.
No Preview Available