Declarative Bias: An Overview (1990)
by Stuart J. Russell and Benjamin N. Grosof
Abstract:
This paper describes and places in context a continuing research
program aimed at constructing effective, autonomous learning systems.
We emphasize the role of knowledge that the system itself possesses in
generating and selecting among inductive hypotheses. Inductive
learning has often been characterized as a search in a hypothesis
space for hypotheses consistent with observations. It is shown that
committing to a given hypothesis space is equivalent to believing a
certain logical sentence --- the declarative bias. We show how many
kinds of declarative bias can be relatively efficiently represented
and derived from background knowledge, and discuss possibilities and
problems for building complete learning systems.
Last update: 1-8-98
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