The AAAI Classic Paper award honors the author(s) of paper(s) deemed most
influential, chosen from a specific conference year. Each year, the time
period considered will advance by one year. The 2006 award will be given
to the most influential paper(s) from the Sixth National Conference on
Artificial Intelligence, held in 1987 in Seattle, Washington.
Papers were judged on the basis of impact, for example:
- Started a new research (sub)area
- Led to important applications
- Answered a long-standing question/issue or clarified what had been murky
- Made a major advance that figures in the history of the subarea
- Has been picked up as important and used by other areas within (or outside of) AI
- Has been very heavily cited
Honorable Mention Co-recipients: Judea Pearl and Thomas Verma
"The Logic of Representing Dependencies by Directed Graphs," presented
at the Sixth National Conference on Artificial Intelligence (AAAI-87),
Seattle, Washington
Data-dependencies of the type "x can tell us more about y
given that we already know z" can be represented in various
formalisms: Probabilistic Dependencies, Embedded-Multi-Valued Dependencies,
Undirected Graphs and Directed-Acyclic Graphs (DAGs). This paper provides
an axiomatic basis, called a semi-graphoid which captures the structure
common to all four types of dependencies and explores the expressive
power of DAGs in representing various types of data dependencies. It
is shown that DAGs can represent a richer set of dependencies than
undirected graphs, that DAGs completely represent the closure of their
specification bases, and that they offer an effective computational device
for testing membership in that closure as well as inferring new dependencies
from given inputs. These properties might explain the prevailing use of
DAGs in causal reasoning and semantic nets.
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(http://www.aaai.org/Awards/classic.php)