Jeremy Smith

2003 Complex Systems Summer School

Statement of current research interests and comments about why I want to attend the school.

Introduction

I am a professional computer programmer with an avid interest in complexity. I am on a self-styled sabbatical this year, and am steeping myself in this field by reading and programming, with a long-term view to working/researching. I may go back to school and pursue a post-graduate degree, or I may continue in industry (or both). I feel this class would be the perfect consolidation of my studies. I present the following, as such, in order to give a little context to my passion for this field.

Story

After we’d all graduated from college (Botany and Chemistry, London 1976), my best friend went to Thailand for some adventure travel. Whilst wandering around in the jungle for a while, he became enamoured by the fine folks in a Theravedan Buddhist monastery, and stayed for a few years. He eventually returned to England, as a shaven-headed, saffron-robed monk, and is now the abbot of a monastery in California.

I, on the other hand, emigrated to the United States, and have been programming computers ever since, all the while wondering, just like my friend, what makes life tick. About ten years ago, just before he turned into an abbot, my friend gave me Mitchell Waldrop’s Complexity to read, which I enjoyed greatly. But it was at a class (in the local Forestry Department) about 6 years ago, where we actually programmed genetic algorithms (amongst other things), that really sent it home.

Since that time, I have been reading lots more, and writing my own models as a way of exploring various and random examples of complex systems. Needless to say, this has been interrupted by details, like my job and family responsibilities, but if I had my druthers, it would be my job.

My path through life and my exploration of it have been anything but straight. Having given up religion at an early age, I managed to survive the New Age and have discovered many exciting breakthroughs of the last decade or two. These include all the exciting avenues of complex adaptive systems, evolutionary psychology, artificial life rather than artificial intelligence, and other related and overlapping fields, and the work and research behind it all. Amongst it all is a new tool – the computer model and the algorithm. (John L Casti expounds on this in his Would-Be Worlds.) The potential of this tool is dawning on more people all the time. With infectious enthusiasm, Stephen Wolfram devotes an entire tome to it (A New Kind of Science) using just eight bits.

Why

I wish to attend the 2003 Complex Systems Summer School to learn, consolidate and hone my knowledge of complex systems. Complex systems pervade reality from simple physical and chemical systems all the way up to our very perceptions.

As understanding of complex systems increases, I believe that modeling will be a valuable tool to validate the steps as they unfold, that using the very techniques nature has used will sharpen our models, and that all of this will help us to explore unnatural techniques, in our attempt to do one better than nature, which will probably only increase our understanding of nature itself.

I attended the Artificial Life Conference last month in Sydney Australia (Alife 8), in order to begin to acquaint myself with the actual people in this field and the kinds of questions they are addressing. I was delighted to see that many questions that have arisen for me, and much of the explorations I have been doing, are indeed being addressed.

Interests

One of my interests is to complete enough artificial plant life (emulating Prusinkiewicz’s work) so that I can explore aspects of alternative evolutionary paths, either on this planet (probably modeling covergent evolution), or another planet (such as in a binary star system). Although this is a nice discrete project, there are two issues that seem to be screaming for attention. At one end is understanding various facets of the computer modeling process itself. And at the other end, human culture and human activity beg for exploration.

I am continuing to understand and explore randomness, chaos, algorithms, and emergence. There was a paper at Alife 8 addressing the modeling of analog or continuous phenomena using the intrinsically discrete or digital computer. Can we detect in our models randomness from our RNGs as opposed to randomness inherent in the computer and in numbers? Visualizing results is essentially translating data into an intuitive ‘picture’. How do we make multidimensional data into a picture or map that is intuitive to our mind, which has evolved to intuit only 3 spatial dimensions? (This was a whole workshop at Alife 8, with more planned.) Why is it intuitive to present data visually rather than aurally, using soundscapes? And yet music is far more poplar in culture – people flock to concerts but not to art galleries.

The evolutionary psychologists stress that we are evolved to succeed in the African savannah. Does this mean that the most intuitive scenario is life as a enacted out on the savannah? Should we not therefore try and reduce results into a story as if enacted out on the African savannah, in duodecaphonic sound and hot and heady smellovision with a full compliment of gossiping relatives?

What do things emerge from? Atoms or units? Many things can be reduced to units, obvious ones being populations, particles and agents. But what about apparent emergent systems like mind, culture, and ecosystems? Perhaps there are units, just very hard to isolate, like quarks and memes.

Living things have evolved to learn about the environment and make predictions from it. Memory, as implemented by the nervous system, greatly augments this. It seems that consciousness is an emergent system, and that memory is a key component. Both memory and pain become completely ineffectual at durations less than a few milliseconds. Is consciousness a complex system with memory a dynamic sub-unit?

And finally, are not our very perceptions and belief systems complex adaptive systems. The wonderful irony is, if we succeed in modeling these and explaining them to ourselves, are we not feeding the results to our own perceptions and belief systems? Definitely worth exploring, if we’re not strung up first.

One of the hardest tasks is to pose an appropriate question, and indeed this is one of the foundations of science. Having posed a question, techniques are then employed to answer it. In my own experience, I find formulating the question extremely hard. But once a question exists, programming (modeling) can begin. Again, I find that it proceeds extremely slowly, and usually an order of magnitude more than expected. I have often delved into the guts of the software system trying to improve it. (And have waited vainly for 5^th generation languages. I still dream about complex adaptive languages and compilers, but I expect that the chores of life will keep me out of that mess.) I feel my years of practical programming experience has primed me for this next foray.

Again, my intent in taking the Complex Systems class is to get much closer to this field, and the people working in it. The foregoing are questions that burn in my mind and I hope to be better able to collaborate and explore them, and the myriad others arising.