dropped ml

Author: Jason2Brownlee

workspace/05-the-field/techreport-20100115-1.tex

@@ -45,7 +45,7 @@ \section{Introduction}
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 This report provides background for the Clever Algorithms project by defining a taxonomy of the related sub-fields of Artificial Intelligence from which the algorithms are drawn.
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-Section~\ref{sec:artificial_intelligence} introduces the field of Artificial Intelligence in terms of the classical symbolic efforts called \emph{neat AI} and the sub-symbolic and descriptive methods referred to as \emph{scruffy AI}. Section~\ref{sec:natural_computation} presents an orthogonal field to AI called Natural Computing that intersects AI with the field of \emph{Biologically Inspired Computation}. Section~\ref{sec:computationl_intelligence} introduces the field of \emph{Computational Intelligence} as an effort that unifies a number of descriptive AI sub-fields such as evolutionary computation, fuzzy logic, and neural networks. Section~\ref{sec:metaheuristics} considers the heuristic perspective on Computational Intelligence methods and the more recent fields of \emph{Metaheuristics} and \emph{Hyperheuristics}. Section~\ref{sec:machine_learning} looks at the sister field of Machine Learning, and highlights the differences between statistical and heuristic methods. Finally, Section~\ref{sec:clever_algorithms} introduces so-named \emph{clever algorithms} from the Clever Algorithms Project and how they relate to the canonical taxonomy of Artificial Intelligence sub-fields introduced in this report.
+Section~\ref{sec:artificial_intelligence} introduces the field of Artificial Intelligence in terms of the classical symbolic efforts called \emph{neat AI} and the sub-symbolic and descriptive methods referred to as \emph{scruffy AI}. Section~\ref{sec:natural_computation} presents an orthogonal field to AI called Natural Computing that intersects AI with the field of \emph{Biologically Inspired Computation}. Section~\ref{sec:computationl_intelligence} introduces the field of \emph{Computational Intelligence} as an effort that unifies a number of descriptive AI sub-fields such as evolutionary computation, fuzzy logic, and neural networks. Section~\ref{sec:metaheuristics} considers the heuristic perspective on Computational Intelligence methods and the more recent fields of \emph{Metaheuristics} and \emph{Hyperheuristics}. Finally, Section~\ref{sec:clever_algorithms} introduces so-named \emph{clever algorithms} from the Clever Algorithms Project and how they relate to the canonical taxonomy of Artificial Intelligence sub-fields introduced in this report.
 
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 % Artificial Intelligence (based on copy from my thesis)
@@ -138,17 +138,6 @@ \section{Metaheuristics}
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 Hyperheuristics are yet another extension that focus on heuristics that modify their parameters (online or offline) to improve the efficacy of solution or efficiency of the computation. Hyperheuristics provide high-level strategies that may employ machine learning and adapt their search behavior by modifying the application of the sub-procedures or even which procedures are used (operating on the space of heuristics which in turn operate within the problem domain) \cite{Burke2003a, Burke2003}. 
 
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-% Machine Learning
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-\section{Machine Learning}
-\label{sec:machine_learning}
-Another important perspective is that provided by the field of Machine Learning that focuses on the learning properties of Artificial Intelligence. The term is commonly used to describe inductive model building techniques (that generalize from specific observations) that are applied to ‘learn’ relationships in data sets (the application of which is referred to as Data Mining [433]), with or without supervision (corrective behavior) [293].
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-\subsection{Statistical Machine Learning}
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-\subsection{Data Mining}
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