% \section{Cyc}
% A great deal of work with the Semantic Web is trying to get Semantic Nets working. I have no idea where this will go, if anywhere. Perhaps the largest semantic net out there is Cyc, about which I know nothing

\section{WhyNot}
WhyNot \cite{chalupsky02whynot} is a tool which is part of an inference system whose purpose is to be more ambitious than AIR currently is. While AIR rules should always generate a result, and then returns the proof for the result, WhyNot is concerned with failed queries in a reasoning engine. WhyNot tries to find what is likely missing from failed queries. In doing so, it tries to return what is \emph{plausibly} the indended result, as well as why it did not work, for some definition of plausible. This is hard, and in the general case intractible, but in many cases a reasonable result can be generated.

Both WhyNot \cite{chalupsky02whynot} and the Know system
\cite{kapadia04know} focus explicitly on failed queries and try to
suggest changes to the knowledge base that will cause these queries to
succeed.  Our justification approach is more general and allows
failures to be captured in policies so explanations can be provided
for both successful and failed policy decisions.

\section{InferenceWeb}
The reserchers at Stanford were interested in a general proof format. The result is IntferenceWeb \cite{mcguinness04iw}, a format for representing inferences and proofs. This is orthogonal my work to generate and prove those inferences.

\section{Python-DLP}
The Python-DLP \cite{python-dlp} project is interested in the intersection of DL and Horn clauses. This is the set of DL statements that can be represented with Horn rules.The FUXI project within Python-DLP has a a RETE based reasoner to process these. They are thus much more interested in DL than in rules, although by using rules to process the DL allows for combining it with other rules. They have defined a semantics for Notation3 rules \cite{FUXI-semantics}, which mainly disallows implying existentials, which would give an expressivity greater than datalog. 
