Probability and plurality for aggregations of learning machines

Leonard Pitt; Carl H. Smith

doi:10.1016/0890-5401(88)90046-6

Probability and plurality for aggregations of learning machines

Leonard Pitt, Carl H. Smith

Research output: Contribution to journal › Article › peer-review

Abstract

A new notion of probabilistic team inductive inference is introduced and compared with both probabilistic inference and team inference. In many cases, but not all, probabilism can be traded for pluralism, and vice versa. Necessary and sufficient conditions are given describing when a team of deterministic or probabilistic learning machines can be coalesced into a single learning machine. A subtle difference between probabilism and pluralism is revealed.

Original language	English (US)
Pages (from-to)	77-92
Number of pages	16
Journal	Information and Computation
Volume	77
Issue number	1
DOIs	https://doi.org/10.1016/0890-5401(88)90046-6
State	Published - Apr 1988
Externally published	Yes

ASJC Scopus subject areas

Theoretical Computer Science
Information Systems
Computer Science Applications
Computational Theory and Mathematics

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10.1016/0890-5401(88)90046-6

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Probability and plurality for aggregations of learning machines

Abstract

ASJC Scopus subject areas

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