converted to XeLaTeX & more Intro

arbeit/Makefile

@@ -1,11 +1,11 @@
 all: ma.md bibma.bib template.tex settings/abkuerzungen.tex settings/commands.tex settings/environments.tex settings/hyphenation.tex settings/packages.tex files/titlepage.tex files/erklaerung.tex
 	pandoc -s -N --template=template.tex ma.md -o ma.tex
 	rm -f ma.pdf ma.aux ma.idx ma.lof ma.log ma.lot ma.out ma.tdo ma.toc ma.bbl ma.blg ma.loa
-	pdflatex -interaction batchmode ma.tex || true
+	xelatex -interaction batchmode ma.tex || true
 	bibtexu ma
-	pdflatex -interaction batchmode ma.tex || true
+	xelatex -interaction batchmode ma.tex || true
 	while test `cat ma.log | grep -e "\(Rerun to get citations correct\)" | wc -l` -gt 0 ; do \
-		rm ma.log && (pdflatex -interaction batchmode ma.tex || true) \
+		rm ma.log && (xelatex -interaction batchmode ma.tex || true) \
 	done
 	rm -f ma.aux ma.idx ma.lof ma.lot ma.out ma.tdo ma.toc ma.bbl ma.blg ma.loa
 	# rm -f ma.log

arbeit/TODO.md

@@ -1,6 +1,9 @@
 10x10x10 3x variablität errechnen
     - variablität soll sich unterscheiden -> Plot
     - Punkte in der Mitte tragen nichts zur Parametrisierung bei, da zu weit weg
-4x5x4, 4x4x7 100x rechnen + plotten
+
+4x4x5, 7x4x4 100x rechnen + plotten
+ - 1. done, 2. rechnet
 
 1D-Fall noch 7x4, 4x7 und 7x7 als hochauflösendes.
+ - done

arbeit/bibma.bib

@@ -87,3 +87,31 @@ doi = {10.1137/0111030},
 URL = {https://doi.org/10.1137/0111030},
 eprint = {https://doi.org/10.1137/0111030}
 }
+@article{minai2006complex,
+  title={Complex engineered systems: A new paradigm},
+  author={Minai, Ali A and Braha, Dan and Bar-Yam, Yaneer},
+  journal={Complex engineered systems: Science meets technology},
+  pages={1--21},
+  year={2006},
+  publisher={Springer},
+  url={https://www.researchgate.net/profile/Yaneer_Bar-Yam/publication/225104044_Complex_Engineered_Systems_A_New_Paradigm/links/59107f20a6fdccbfd57eb84d/Complex-Engineered-Systems-A-New-Paradigm.pdf}
+}
+@article{wagner1996complex,
+  title={COMPLEX ADAPTATIONS AND THE EVOLUTION OF EVOLVABILITY},
+  author={WAGNER, GUNTER P and ALTENBERG23, LEE},
+  journal={Evolution},
+  volume={50},
+  number={3},
+  pages={967--976},
+  year={1996},
+  url={http://arep.med.harvard.edu/pdf/Wagner96.pdf},
+}
+@inproceedings{richter2015evolvability,
+  title={Evolvability of representations in complex system engineering: a survey},
+  author={Richter, Andreas and Botsch, Mario and Menzel, Stefan},
+  booktitle={Evolutionary Computation (CEC), 2015 IEEE Congress on},
+  pages={1327--1335},
+  year={2015},
+  organization={IEEE},
+  url={http://www.graphics.uni-bielefeld.de/publications/cec15.pdf}
+}

arbeit/files/erklaerung.tex

@@ -2,11 +2,10 @@
 \thispagestyle{empty}
 \vspace*{\stretch{1}}
 \noindent
-{\huge Erklärung}\\[1cm]
+{\huge Declaration of own work(?)}\\[1cm]
 I hereby declare that this thesis is my own work and effort. Where other sources of information have been used, they have been acknowledged.
-blah blah
+\improvement[inline]{write proper declaration..}
-
+%\\[2cm]
-\\[2cm] 
 Bielefeld, den \today\hspace{\fill}
 \parbox[t]{5cm}{\dotfill\\ \centering Stefan Dresselhaus}
 \vspace*{\stretch{3}}

arbeit/ma.md

@@ -24,20 +24,54 @@ Unless otherwise noted the following holds:
 # Introduction
 
 \improvement[inline]{mehr Motivation, Ziel der Arbeit, Wieso das ganze?\newline
-Wieso untersuchen wir das überhaupt?\newline
+Wieso untersuchen wir das überhaupt? \cmark \newline
+Aufbau der Arbeit? \xmark \newline
 Mehr Bilder}
 
-In this Master Thesis we try to extend a previously proposed concept of
+Many modern industrial design processes require advanced optimization methods
-predicting the evolvability of \acf{FFD} given a
+do to the increased complexity. These designs have to adhere to more and more
-Deformation-Matrix\cite{anrichterEvol}. In the original publication the author
+degrees of freedom as methods refine and/or other methods are used. Examples for
-used random sampled points weighted with \acf{RBF} to deform the mesh and
+this are physical domains like aerodynamic (i.e. drag), fluid dynamics (i.e.
-defined three different criteria that can be calculated prior to using an
+throughput of liquid) -- where the complexity increases with the temporal and
-evolutional optimization algorithm to asses the quality and potential of such
+spatial resolution of the simulation -- or known hard algorithmic problems in
-optimization.
+informatics (i.e. layouting of circuit boards or stacking of 3D-objects).
+Moreover these are typically not static environments but requirements shift over
+time or from case to case.
+
+Evolutional algorithms cope especially well with these problem domains while
+addressing all the issues at hand\cite{minai2006complex}. One of the main
+concerns in these algorithms is the formulation of the problems in terms of a
+genome and a fitness function. While one can typically use an arbitrary
+cost-function for the fitness-functions (i.e. amount of drag, amount of space,
+etc.), the translation of the problem-domain into a simple parametric
+representation can be challenging.
+
+The quality of such a representation in biological evolution is called
+*evolvability*\cite{wagner1996complex} and is at the core of this thesis.
+However, there is no consensus on how *evolvability* is defined and the meaning
+varies from context to context\cite{richter2015evolvability}.
+
+As we transfer the results of Richter et al.\cite{anrichterEvol} from using
+\acf{RBF} as a representation to manipulate a geometric mesh to the use of
+\acf{FFD} we will use the same definition for evolvability the original author
+used, namely *regularity*, *variability*, and *improvement potential*. We
+introduce these term in detail in Chapter \ref{sec:intro:rvi}.
+
+In the original publication the author used random sampled points weighted with
+\acf{RBF} to deform the mesh and showed that the mentioned criteria of
+*regularity*, *variability*, and *improvement potential* correlate with the quality
+and potential of such optimization.
 
 We will replicate the same setup on the same meshes but use \acf{FFD} instead of
-\acf{RBF} to create a deformation and evaluate if the evolution-criteria still
+\acf{RBF} to create a local deformation near the control points and evaluate if
-work as a predictor given the different deformation scheme.
+the evolution-criteria still work as a predictor given the different deformation
+scheme, as suspected in \cite{anrichterEvol}.
+
+## Outline of this thesis
+
+\improvement[inline]{Kapitel vorstellen, Inhalt? Ziel?}
+
+# Background
 
 ## What is \acf{FFD}?
 \label{sec:intro:ffd}
@@ -150,6 +184,7 @@ optimization has one more advantage as you get bad solutions fast, which refine
 over time.
 
 ## Criteria for the evolvability of linear deformations
+\label{sec:intro:rvi}
 
 ### Variability
 
@@ -286,7 +321,7 @@ To solve this we derive partially, like before:
 $$
 \begin{array}{rl}
     \displaystyle \frac{\partial Err_x}{\partial u} & p^{*}_x - \displaystyle \sum_i \sum_j \sum_k N_{i,d,\tau_i}(u) N_{j,d,\tau_j}(v) N_{k,d,\tau_k}(w) \cdot {c_{ijk}}_x \\
-  = & \displaystyle - \sum_i \sum_j \sum_k N'_i(u) N_{j,d,\tau_j}(v) N_{k,d,\tau_k}(w) \cdot {c_{ijk}}_x
+  = & \displaystyle - \sum_i \sum_j \sum_k N'_{i,d,\tau_i}(u) N_{j,d,\tau_j}(v) N_{k,d,\tau_k}(w) \cdot {c_{ijk}}_x
 \end{array}
 $$
 
@@ -302,10 +337,17 @@ J(Err(u,v,w)) =
 \end{array}
 \right)
 $$
-
+$$
-\unsure[inline]{Should I add an informal complete derivative?\newline
+\scriptsize
-Like leaving out Sums & $i,j,k$-Indices to make obvious what derivative belongs
+=
-where in what case?}
+\left(
+\begin{array}{ccc}
+- \displaystyle \sum_{i,j,k} N'_{i}(u) N_{j}(v) N_{k}(w) \cdot {c_{ijk}}_x &- \displaystyle \sum_{i,j,k} N_{i}(u) N'_{j}(v) N_{k}(w) \cdot {c_{ijk}}_x & - \displaystyle \sum_{i,j,k} N_{i}(u) N_{j}(v) N'_{k}(w) \cdot {c_{ijk}}_x \\
+- \displaystyle \sum_{i,j,k} N'_{i}(u) N_{j}(v) N_{k}(w) \cdot {c_{ijk}}_y &- \displaystyle \sum_{i,j,k} N_{i}(u) N'_{j}(v) N_{k}(w) \cdot {c_{ijk}}_y & - \displaystyle \sum_{i,j,k} N_{i}(u) N_{j}(v) N'_{k}(w) \cdot {c_{ijk}}_y \\
+- \displaystyle \sum_{i,j,k} N'_{i}(u) N_{j}(v) N_{k}(w) \cdot {c_{ijk}}_z &- \displaystyle \sum_{i,j,k} N_{i}(u) N'_{j}(v) N_{k}(w) \cdot {c_{ijk}}_z & - \displaystyle \sum_{i,j,k} N_{i}(u) N_{j}(v) N'_{k}(w) \cdot {c_{ijk}}_z
+\end{array}
+\right)
+$$
 
 With the Gauss-Newton algorithm we iterate via the formula
 $$J(Err(u,v,w)) \cdot \Delta \left( \begin{array}{c} u \\ v \\ w \end{array} \right) = -Err(u,v,w)$$
@@ -319,6 +361,9 @@ linear equations.
   - Deformation ist um einen Kontrollpunkt viel direkter zu steuern.
   - => DM-FFD?
 
+
+# Scenarios for testing evolvability criteria using \acf{FFD}
+
 ## Test Scenario: 1D Function Approximation
 
 ### Optimierungszenario

arbeit/ma.tex

@@ -148,18 +148,60 @@ Unless otherwise noted the following holds:
 
 \chapter{Introduction}\label{introduction}
 
-In this Master Thesis we try to extend a previously proposed concept of
+\improvement[inline]{mehr Motivation, Ziel der Arbeit, Wieso das ganze?\newline
-predicting the evolvability of \acf{FFD} given a
+Wieso untersuchen wir das überhaupt? \cmark \newline
-Deformation-Matrix\cite{anrichterEvol}. In the original publication the
+Aufbau der Arbeit? \xmark \newline
-author used random sampled points weighted with \acf{RBF} to deform the
+Mehr Bilder}
-mesh and defined three different criteria that can be calculated prior
+
-to using an evolutional optimization algorithm to asses the quality and
+Many modern industrial design processes require advanced optimization
-potential of such optimization.
+methods do to the increased complexity. These designs have to adhere to
+more and more degrees of freedom as methods refine and/or other methods
+are used. Examples for this are physical domains like aerodynamic
+(i.e.~drag), fluid dynamics (i.e.~throughput of liquid) -- where the
+complexity increases with the temporal and spatial resolution of the
+simulation -- or known hard algorithmic problems in informatics
+(i.e.~layouting of circuit boards or stacking of 3D-objects). Moreover
+these are typically not static environments but requirements shift over
+time or from case to case.
+
+Evolutional algorithms cope especially well with these problem domains
+while addressing all the issues at hand\cite{minai2006complex}. One of
+the main concerns in these algorithms is the formulation of the problems
+in terms of a genome and a fitness function. While one can typically use
+an arbitrary cost-function for the fitness-functions (i.e.~amount of
+drag, amount of space, etc.), the translation of the problem-domain into
+a simple parametric representation can be challenging.
+
+The quality of such a representation in biological evolution is called
+\emph{evolvability}\cite{wagner1996complex} and is at the core of this
+thesis. However, there is no consensus on how \emph{evolvability} is
+defined and the meaning varies from context to
+context\cite{richter2015evolvability}.
+
+As we transfer the results of Richter et al.\cite{anrichterEvol} from
+using \acf{RBF} as a representation to manipulate a geometric mesh to
+the use of \acf{FFD} we will use the same definition for evolvability
+the original author used, namely \emph{regularity}, \emph{variability},
+and \emph{improvement potential}. We introduce these term in detail in
+Chapter \ref{sec:intro:rvi}.
+
+In the original publication the author used random sampled points
+weighted with \acf{RBF} to deform the mesh and showed that the mentioned
+criteria of \emph{regularity}, \emph{variability}, and \emph{improvement
+potential} correlate with the quality and potential of such
+optimization.
 
 We will replicate the same setup on the same meshes but use \acf{FFD}
-instead of \acf{RBF} to create a deformation and evaluate if the
+instead of \acf{RBF} to create a local deformation near the control
-evolution-criteria still work as a predictor given the different
+points and evaluate if the evolution-criteria still work as a predictor
-deformation scheme.
+given the different deformation scheme, as suspected in
+\cite{anrichterEvol}.
+
+\section{Outline of this thesis}\label{outline-of-this-thesis}
+
+\improvement[inline]{Kapitel vorstellen, Inhalt? Ziel?}
+
+\chapter{Background}\label{background}
 
 \section{\texorpdfstring{What is \acf{FFD}?}{What is ?}}\label{what-is}
 
@@ -281,6 +323,8 @@ you get bad solutions fast, which refine over time.
 \section{Criteria for the evolvability of linear
 deformations}\label{criteria-for-the-evolvability-of-linear-deformations}
 
+\label{sec:intro:rvi}
+
 \subsection{Variability}\label{variability}
 
 In \cite{anrichterEvol} variability is defined as
@@ -424,7 +468,7 @@ To solve this we derive partially, like before:
 \[
 \begin{array}{rl}
     \displaystyle \frac{\partial Err_x}{\partial u} & p^{*}_x - \displaystyle \sum_i \sum_j \sum_k N_{i,d,\tau_i}(u) N_{j,d,\tau_j}(v) N_{k,d,\tau_k}(w) \cdot {c_{ijk}}_x \\
-  = & \displaystyle - \sum_i \sum_j \sum_k N'_i(u) N_{j,d,\tau_j}(v) N_{k,d,\tau_k}(w) \cdot {c_{ijk}}_x
+  = & \displaystyle - \sum_i \sum_j \sum_k N'_{i,d,\tau_i}(u) N_{j,d,\tau_j}(v) N_{k,d,\tau_k}(w) \cdot {c_{ijk}}_x
 \end{array}
 \]
 
@@ -440,12 +484,18 @@ J(Err(u,v,w)) =
 \frac{\partial Err_z}{\partial u} & \frac{\partial Err_z}{\partial v} & \frac{\partial Err_z}{\partial w}
 \end{array}
 \right)
+\] \[
+\scriptsize
+=
+\left(
+\begin{array}{ccc}
+- \displaystyle \sum_{i,j,k} N'_{i}(u) N_{j}(v) N_{k}(w) \cdot {c_{ijk}}_x &- \displaystyle \sum_{i,j,k} N_{i}(u) N'_{j}(v) N_{k}(w) \cdot {c_{ijk}}_x & - \displaystyle \sum_{i,j,k} N_{i}(u) N_{j}(v) N'_{k}(w) \cdot {c_{ijk}}_x \\
+- \displaystyle \sum_{i,j,k} N'_{i}(u) N_{j}(v) N_{k}(w) \cdot {c_{ijk}}_y &- \displaystyle \sum_{i,j,k} N_{i}(u) N'_{j}(v) N_{k}(w) \cdot {c_{ijk}}_y & - \displaystyle \sum_{i,j,k} N_{i}(u) N_{j}(v) N'_{k}(w) \cdot {c_{ijk}}_y \\
+- \displaystyle \sum_{i,j,k} N'_{i}(u) N_{j}(v) N_{k}(w) \cdot {c_{ijk}}_z &- \displaystyle \sum_{i,j,k} N_{i}(u) N'_{j}(v) N_{k}(w) \cdot {c_{ijk}}_z & - \displaystyle \sum_{i,j,k} N_{i}(u) N_{j}(v) N'_{k}(w) \cdot {c_{ijk}}_z
+\end{array}
+\right)
 \]
 
-\unsure[inline]{Should I add an informal complete derivative?\newline
-Like leaving out Sums & $i,j,k$-Indices to make obvious what derivative belongs
-where in what case?}
-
 With the Gauss-Newton algorithm we iterate via the formula
 \[J(Err(u,v,w)) \cdot \Delta \left( \begin{array}{c} u \\ v \\ w \end{array} \right) = -Err(u,v,w)\]
 and use Cramers rule for inverting the small Jacobian and solving this
@@ -463,6 +513,10 @@ system of linear equations.
   =\textgreater{} DM-FFD?
 \end{itemize}
 
+\chapter{\texorpdfstring{Scenarios for testing evolvability criteria
+using
+\acf{FFD}}{Scenarios for testing evolvability criteria using }}\label{scenarios-for-testing-evolvability-criteria-using}
+
 \section{Test Scenario: 1D Function
 Approximation}\label{test-scenario-1d-function-approximation}
 

arbeit/settings/commands.tex

@@ -131,25 +131,6 @@
 \newcommand{\myquote}[1]{\glqq{}#1\grqq{}} % richtige Anfuehrungszeichen: ,, Bla ''
 % \newcommand{\str}[1]{{\tt{}#1}} % einheitliche formatierung fuer zeichenketten
 
-% ##### draft #####
-\newcommand{\ignore}[1]{}
-\newcommand\info[1]{\marginpar{\begin{center}#1\end{center}}}
-\newcommand\note{\marginpar{\begin{center}$\longleftarrow$\end{center}}}
-\newcommand\picmis[1]{$$\boxed{\mbox{\ttfamily picture #1}}$$}
-%Todo am Rand notieren
-\begin{comment}
-% DONE WITH \usepackage{todo}
-\newcommand{\todo}[1]{%
-  \ensuremath{\bigstar}%
-  \marginpar{%
-		\begin{flushleft}%
-			\vspace{-1.5\baselineskip}%
-			{\small TODO\ \ensuremath{\bigstar}\\#1}%
-		\end{flushleft}%
-  }%
-}%
-\end{comment}
-
 \newcommand\opdown[2]{\lower0.75em\hbox{$\stackrel{\displaystyle#1}{\scriptstyle#2}$}}
 \newcommand\toconv[2]{\;\lower0.5em\hbox{$\stackrel{\longrightarrow}{\scriptstyle#1\to#2}$}}
 \newcommand\wildcard[1]{\fbox{\ttfamily Platzhalter: #1}}
@@ -179,3 +160,6 @@
 \newcommandx{\info}[2][1=]{\todo[linecolor=OliveGreen,backgroundcolor=OliveGreen!25,bordercolor=OliveGreen,#1]{\textbf{Info:} #2}}
 \newcommandx{\improvement}[2][1=]{\todo[linecolor=violet,backgroundcolor=violet!25,bordercolor=violet,#1]{\textbf{Improvement:} #2}}
 \newcommandx{\thiswillnotshow}[2][1=]{\todo[disable,#1]{#2}}
+
+\renewcommand\cmark{\textcolor{OliveGreen}{\ding{51}}}
+\renewcommand\xmark{\textcolor{Maroon}{\ding{55}}}

arbeit/settings/packages.tex

@@ -1,3 +1,4 @@
+\usepackage[dvipsnames]{xcolor}
 \usepackage{acronym}					% acronym list and writing acronyms full length exactly once
 % \usepackage{amsfonts}
 \usepackage{amsmath}					%\align
@@ -15,7 +16,7 @@
 \usepackage{color}						%\colorbox
 \usepackage{dsfont}						%\mathds
 \usepackage{draftwatermark}
-\SetWatermarkLightness{0.95} % default: 0.8
+\SetWatermarkLightness{0.9} % default: 0.8
 \usepackage{epigraph}
 % \usepackage{euler}  					% euler: uni, eucal: baake, ohne: standard
 \usepackage{eucal}						% euler calligraphy
@@ -36,11 +37,11 @@
 \usepackage{mathtools}
 \usepackage{multirow}
 \usepackage{nicefrac}
-\usepackage[numbers,square,sort=none]{natbib}
+\usepackage[numbers,square,sort]{natbib}
-\newcommand*{\refname}{References}
 \usepackage{patchcmd}
 %\usepackage[draft]{pdfpages}
 \usepackage{pdfpages}
+\usepackage{pifont}
 %\usepackage{pst-all}					% PSTricks-Grafikerstellung
 %\usepackage{pstricks}
 %\usepackage{qtree}						% baum
@@ -62,7 +63,6 @@
 \usepackage{verbatim} % \begin{comment} \end{comment}
 \usepackage{wrapfig}
 % \usepackage{wasysym}
-\usepackage[pdftex,dvipsnames]{xcolor}
 \usepackage{xspace}						% intelligent \makro_ whitespace
 \usepackage{xargs}                      % use more than one optional parameter in new commands