added ais to ci

Author: Jason2Brownlee

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

@@ -91,7 +91,9 @@ \subsection{Computation with Biology}
 % 
 \section{Computational Intelligence}
 \label{sec:computationl_intelligence}
-A modern name for the sub-field of AI concerned with sub-symbolic (messy, scruffy, soft) mechanisms is Computational Intelligence. This name provides a banner which groups four principle approaches: Fuzzy Intelligence, Connectionist Intelligence, Evolutionary Intelligence, and Swarm Intelligence \cite{Engelbrecht2007, Pedrycz1997}. Generally, Computational Intelligence describes techniques that focus on \emph{strategy} and \emph{outcome}. This section provides a summary of the four primary areas of study in Computational Intelligence.
+A modern name for the sub-field of AI concerned with sub-symbolic (messy, scruffy, soft) mechanisms is Computational Intelligence. This name provides a banner which groups four principle approaches: Fuzzy Intelligence, Connectionist Intelligence, Evolutionary Intelligence, and Swarm Intelligence \cite{Engelbrecht2007, Pedrycz1997}. Generally, Computational Intelligence describes techniques that focus on \emph{strategy} and \emph{outcome}. 
+% examples
+Computational Intelligence broadly covers sub-disciplines that focus on adaptive and intelligence systems, not limited to: evolutionary computation, Swarm Intelligence (Particle Swarm and Ant Colony Optimization), Fuzzy Systems, Artificial Immune Systems, and Artificial Neural Networks. This section provides a brief summary of the each of the five primary areas of study.
 
 \subsection{Evolutionary Computation} 
 A paradigm that is concerned with the investigation of systems inspired by the neo-Darwinian theory of evolution by means of natural selection. Popular evolutionary algorithms include the Genetic Algorithm, Evolution Strategy, Genetic and Evolutionary Programming, and Differential Evolution \cite{Baeck2000, Baeck2000a}. The evolutionary process is considered an adaptive strategy and is typically applied to search and optimization domains \cite{Goldberg1989, Holland1975}.
@@ -105,6 +107,9 @@ \subsection{Artificial Neural Networks}
 \subsection{Fuzzy Intelligence}
 An approach that is concerned with the investigation of fuzzy logic which is a form of logic that is not constrained to true and false like propositional logic, but rather functions which define approximate truth or degree’s of truth \cite{Zadeh1996}. Fuzzy logic and fuzzy systems are a logic system used as a reasoning strategy and are typically applied to expert system and control system domains.
 
+\subsection{Artificial Immune Systems}
+A collection of approaches inspired by the structure and function of the acquired immune system of vertebrates. Popular approaches include clonal selection, negative selection, dendritic cell algorithm, and immune network algorithms. The immune-inspired adaptive processes are varied and show similarities to evolutionary computation and artificial neural networks, and are typically used for optimization and pattern recognition domains \cite{Castro2002}.  
+
 % 
 % Metaheuristics
 % 

workspace/bibtex.bib

@@ -124,6 +124,15 @@ @ARTICLE{Burke2003
   timestamp = {2010.01.15}
 }
 
+@BOOK{Castro2002,
+  title = {Artificial Immune Systems: A New Computational Intelligence Approach},
+  publisher = {Springer},
+  year = {2002},
+  author = {Leandro N. de Castro and Jonathan Timmis},
+  owner = {jasonb},
+  timestamp = {2010.01.15}
+}
+
 @INBOOK{Castro2005a,
   chapter = {From biologically inspired computing to natural computing},
   title = {Recent developments in biologically inspired computing},