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\author{Jordan Perr}

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\begin{abstract}
The mechanistic philosophy of the nature of inteligence and free will suggests that all beings (living or nonliving) are at the very basic level systems of imbalance. This study will attempt to create a non carbon based system whose output given a set of input is indistinguishable from the output of a carbon based ``life'' form. I will employ the use of evolutionary algorithms to constantly morph my creature into better and better physical versions. Hypergraphs will be used to store behavioral characteristics, and will be modified from version to version through both random evolutionary mutation as well as by sophisticated machine learning algorithms. The feedback on which generations of my organism will be graded will be gathered by probing key parameters in a three dimensional spacial simulation.
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\section{Introduction}

Following that definition of life, one might suggest that there is nothing more ``alive'' about the behavior of a human being than of the way air masses traverse the globe. Both systems react in complex ways given countless stimuli, and both systems are only partially understood by the scientific community. This way of classifying ``life'' will be assumed throughout the project and will play a key role in my approach to experimentation and in the construction of this paper.

Let us observe a system which common sense would call abiotic. Lets take, for example, the atmosphere. This macroscopic body of gasses is constantly shifting and churning, constantly pushing past other parts of itself, all driven by the constant turning on the earth. Just as the plankton's chemical processes are fuelled by the sun, the air mass' activities are fueled by the sun's energy and by the rotation of the earth. As the earth's oceans warm, the atmosphere act differently as if it's ``responding'' to this environmental stimulus. As a more extrapolated example: As single celled parmecium pinch prey out of their surroundings via Phagocytosis, the Earth's atmosphere discharges electricity buildup in an equally awe-inspriring and complex (if not macroscopic) way.

Let us now observer a system which common sense would call biotic. Forget about gray-area subjects like free will and thought. Focus on something much more basic and easy to understand. Pick the simplest single celled creature you can imagine. Parmecium, Amoeba, Bacteria, or Planktons. Biology has fully explored and understood every chemical process which goes on inside those single celled creatures. We understand how chemicals are actively transported through membranes, food and waste diffuses through others, and the cell preforms simple actions like Phagocytosis to consume prey, and exactly how (chemically) the cell reacts to stimulus. No magic, no ``higher consciousness,'' just chemical reactions. As the atmosphere acts differently given a warming sea, so will the single celled ``life forms'' which call the ocean their home. In an equaly complex manner (though much more compact) the single celled creature will go through as many changes as the atmosphere of the earth given this subtle environmental change.

It is therefore silly to classify abiotic systems any differently from biotic life forms. I will therefore use the word ``system'' to represent every abiotic and biotic system observed. I will define the word ``Life'' as what popular scientific and public belief in the year 2009 would dictate, and the same type of definition will hold for ``abiotic'' and ``biotic''. Namely, carbon based cellular systems which have been evolving into ever more complex systems for millions of years.

\subsection{The Purpose}
This project will perform two important functions. The first is the chance for me personally to research and understand some fundamental concepts in the field of Artificial Inteligence.The second is to possibly redefine ``life'' as we know it and create an abiotic system so complex that the scientiffic community (given key input and output measurement comparisons) could not distinguish the silicon based computer model apart from a carbon based life form. This would effictively produce artificial life (as per my definition) and could then be extended at a later date (or by other people) to become smarter and more robust (thus clearing a path towards the popular image of AI)

\section{The Experiment}

\subsection{Appearance}
 This project has thus been designed with Sexiness in mind. If all goes according to plan, I will create a ``Living, Squirming creature'' where there was previously nothing definable as life. The creature I create will morph after each trial in an attempt to embetter it's ability to complete it's task. Using state of the art optimization algorithms, I can force my creature's physical body to be more and more suited to it's environment. As slight changes are made to the organism, subsequent simulations will yield slightly different results. I will save the state of the organism at each termination so that I can resume evolution at similar stages in the future.

\subsection{The Mind}
 The creature will not only have a physical component, but will have a constantly changing ``mind.'' After careful consideration, I have settled upon using a hypergraph as the data structure to store and manipulate my creature's memories and instincts.

 I am not going to start from scratch, as this would be foolish and impossible to complete. In fact, I will assume that my creature can start off it's learning and evolutionary path with a set of preprogrammed instincts. This is simply an extrapolation of what might have randomly occurred in the sea of primality as random molecules of carbon came together in just the right ways to create a simple hypergraph-like structure.

\section{Research}
Through my reading, I have come accross many prime sources of information. The foremost authority for directing my research attention has been Wikipedia. By stumbling through the links of wikipedia, I have been introduced to such people as Dr. Lawrence J. Fogel, a pioneer in the field of evolutionary algorithm application to machine learning processes.

\subsection{Fogel's Prediction Experiments}
While looking for one of his many published books \cite{fogint} I came upon a powerpoint slideshow by Professor  Marek Andrzej Perkowski from Portland State University. This interesting powerpoint explores the difference between intelligent evolution and physical outperformance through evolution. He uses as evidence for his lesson a series of experiments from Dr. Lawrence J. Fogel. These experiments were (at their simplest definition) an attempt to predict a series of symbols after being exposed to an initial lot of symbols. These machines were then graded on their performance, and the ones who performed above a certain threshhold were allowed to mutate, while the ones who were worse were thrown away. I will study these experiments, as they are closely related to my experiments (yet are much more simplified.) My project will extend upon the work of Dr. Fogel, and will use some of Fogel's findings as starting points.


\section{Materials}
\begin{itemize}
\item A reasonably powerful computer to run organism simulations on. My home laptop is probably powerful enough to run enough simulations, but a more powerful computer would allow more trials, and possibly a better result.
\item Books and papers on evolutionary algorithms and machine learning. I have already ordered Dr. Fogel's ``Intelligence Through Simulated Evolution: Forty Years of Evolutionary Programming'' \cite{fogint}
\item A good and extendable 3d engine to run simulations. This will need to accept models output from my evolution algorithms, and will need to return the results in an easy to parse way. The user must be able to alter the speed of this simulator so that the trials don't take forever. I would also like to be able to take screenshots of the simulation in action at various stages.
\end{itemize}

\section{Timeline}
\begin{itemize}
\item March: Compile tons of research on genetic algos and learning algos.
\item April: Find a 3d simulator which meets my needs
\item April: Experiment with java exporting models and scripts to 3d simulator and back to java for processing dataflow.
\item May: Write evolutionary algorithms in java to parse the output of the 3d simulator and generate new models for the next trial
\item July: Write learning algorithms in java to do the same as the evolutionary algorithms, but working on the hypergraph of the mind.
\item September: Finished all experiments, start writing final paper.
\end{itemize}

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