So Many Schemes

Brief synopsis: Users in the online world of Second Life are playing with Artificial Life — creating dynamic, evolving ecosystems. I predict that we will see continued creation of complex, emergent ecosystems in MMOGs in the future.

I have been playing with Second Life (SL), a realization of the Stephensonian Metaverse. I’m calling this “research,” as I’m surveying the state of MMOG Artificial Intelligence and Artificial Life, but at this point it might as well be play. Yet, Second Life really isn’t a game, it’s more of an online, massively-interactive world. All content is user created with the built-in scripting language (LSL), Havok physics engine, and 3D modeling and animation systems. Users create buildings, vehicles, weapons, clothing, gambling joints, a plethora of shops, and much more. Like first life, it’s very flexible. Some users have even succeeded in making a living selling things in SL and then exchanging the in-game currency for real money.

In terms of AI, the most advanced thing I’ve seen is a tie-in with an implementation of Alicebot. The LSL scripting language lends itself to simple AI because it is based around a model of Finite State Machines — any scripted object can be in a number of different states, and can respond differently to events based on which state it is currently in.

However, what SL really lends itself to is Artificial Life. A user known as Surina Skallagrimson has developed an AL model of fish that swim, shoal (flock), seek out food, gain food preferences, see and evade predators, reproduce, and die if insufficiently fed. She has also met with limited success in passing on genetic information to allow simulated evolution. The main restrictions to progress arise from the many limitations of the LSL scripting language, which has no provisions for long-term memory.

I interviewed Surina in SL (a cool experience) and then she showed me the fish. They flock very naturally, colored by their food preferences. Surina is now working on modifying her code to create birds, which will prey upon the fish. The eggs of AL frogs, created by a different SLer, can also be eaten by the fish. Some of Surina’s schools have existed for months, even though each individual can live for a maximum of four hours. If you want to see the fish for yourself, they swim in the waters around Hypatia 49, 221, but wander as far away as neighboring Themiskyra. A basic SL account is free.

What excites me most about this is the potential for systems like SL to allow people to play with AL in an integrated environment. In such systems, one can actively experiment in 3D on an evolving system. The integration with the Havok physics engine makes complex emergent behavior likely.

A choice quote from a blog article about Surina’s work:

Due to “a bug in the fish causing them to reproduce out of control. It appears the limit for 3 sims full of fish is around 10,000 (Ten thousand) fish… A virus was quickly introduced to kill off the mutant fish before they either crashed the servers or they evolved a way of teleporting to the main grid.”

This all brings me back to a project that I did a while ago in which I created a two-dimensional physics simulation and allowed mass-spring “creatures” to evolve mobility. It was much like the new sodarace system. (I was inspired by the original sodaplay.) Creatures evolved methods of locomotion qualitatively similar to runs, walks, slides, rolls, and hops. AL is exciting because simple rules give rise to incredibly complex behaviors. But we already know that, of course, because we are the result of such a process. (Sorry Kansas Board of Education.) I’d love to see people build complex, evolving AL ecosystems in MMOGs, and I predict that we will see this occur as available in-game CPU time for this sort of process increases.

A little while ago I heard a talk by a Google researcher which boiled down to the following statement: With enough data, many computational problems transform into search problems. For example, if you have an index of a billion web pages, you can make a darn good spell checker because you’ve seen 200 different ways to spell Britney Spears. You can also translate among various human languages because you’ve seen documents in so many different languages. And you can make Google Local or Yahoo Local or MSN Local because you can verify information among many sites — if you see Bob’s Pizza associated with a particular phone number on five sites, that number is probably the number of Bob’s Pizza. My question, then, is what else can you do when you have mind-bendingly large quantities of text?

• Identify trends. For example, BlogPulse. I also experimented with this once and mined common links and phrases from 40,000 LiveJournal posts. This could be implemented on a larger scale, though. Could a program identify a change in rhetoric across an entire region or follow cultural shifts?
• Mine information on people. I’ve seen this done, but never well. (But this is creepy. I’m not sure the world really needs better stalking tools.)
• You can verify links. For example, (shameless plug) my site AbsurdlyCool FreebieFinder finds freebies online while avoiding referral links by verifying links across multiple sites. If a link has an embedded referral ID, it won’t be identical on many sites, and so will be ignored. This could be applied to other domains.

Please comment on other possibilities. What if you have images as well as text?

While I am not really an active gamer, I keep an eye on the state of gaming technology, as well as computer graphics in general. (I wrote about MMOGs earlier.) I have never played any Elder Scrolls games, but their new game, called Oblivion, looks impressive. I watched some preview movies detailing the game’s AI engine and procedurally generated forests, both of which look ambitious and well done. I assume they’re using Hidden Markov Models for the forest generation and weather. I’ll be writing more about the state of game AI soon.

More than anything else, I think that Web 2.0 encapsulates the dawning realization that there is still money in the Internet. During the first dot com boom, the Internet was fun because suddenly everyone and their uncle could make money online. It was sort of a wild west meets low-capital capitalism, and this is happening again. Google has proved that web based advertising is big business, Million Dollar Homepage spawned a million copycats, and everyone wants to make the next del.icio.us.

However, and this is part of what makes Web 2.0 exciting, due to the low-capital nature of creating a web company, it is very difficult to stay on top. Without a true technological advantage, or a physical product, it seems like anyone can simply form a startup with two friends in their garage and displace giants. Granted, this almost certainly isn’t true, but this perception leads to the rise of 20 copycat sites for every successful business. Likewise, for every good idea, there are 10 different renditions of it coming out in beta every week. Only one or two of those are actually going to succeed. It’s crazy, capitalistic, scheming, wild west fun, and it seems to be back. But for how long?

I recently read an article about intrade, a company that lets you buy and sell contracts on future events. In other words, if I think that event X will happen by some date, I buy a contract on it from someone who thinks that it won’t happen. If I’m right, I get money, if I’m wrong, the seller gets money. Yes, this is gambling, although intrade takes a commission instead of acting as the ‘house.’ This is also an example of a predictive market, which, some people claim, is a mechanism for aggregating the collective intelligence of crowds. Google’s doing it, as was the Pentagon until they came to their senses.

In some sense, I agree that markets have astonishing predictive power, but on the other hand, it is a myth that you can’t beat the market. Day traders can and do make money from the stock market, and this fact indicates that there are at least fluctuations in the accuracy of market predictions. The predictions are biased by human whim and fancy. However, B.K. Marcus (via Dean’s World) makes a strong case for the increased predictive power of funded markets. If the market is funded, it’s price will (hopefully) reflect the sum of people’s self-interested research. People profit if they do good research. He writes:

“The magic of market mechanisms goes well beyond the creation of consensus from a decentralized distribution of local, implicit, sometimes unconscious knowledge — the power of the market lies in its ability to harness the power of self-interest.”

That gives intrade a boost over some of the free, fantasy markets such as Foresight Exchange and Yahoo’s Tech Buzz Game. I’m going to keep an eye on intrade, and maybe even try it.

This summer I taught an informal course through Networking & Systems at Haverford College. The intent of this summer training was to expose the broader computing center staff (along with others) to advanced publishing topics, the cPanel interface, and to demonstrate what is necessary to manage, support and secure dynamic web sites.

While the course is over, these online class notes are thorough and are written to stand alone. They may prove helpful to those wishing to learn about online content delivery, cPanel, Perl, CGI, and online security.

Intelligent Systems is an umbrella discipline focusing on the study of adaptive, smart, AI-based systems. It’s member fields include Machine Learning, classical Artificial Intelligence, Computer Vision, and Robotics. Why should you care about it? Because the field of Intelligent Systems has a lot to offer smart companies and smart web designers.

I am preparing a series of posts about how an understanding of Intelligent Systems can help you build better things. I will write primarily about techniques from Machine Learning, whose focus is the study of numerical and statistical techniques to make computers learn and adapt. I will be writing these articles over the next few weeks, so stay tuned.

To whet your appetite, here are some examples of what these techniques can do: Riya, spam filtering, machine translation, clustering, podcast transcription, OCR, driving directions, and MSN’s new search (’search’ is a machine learning problem). And, of course, Google PageRank, AdSense, Sets, and everything else they do.

I’m thinking about massively multiplayer games. Really, I’ve been thinking about them ever since I was addicted to BatMUD years ago. (I’m ashamed of how many hours I spent on BatMUD. Didn’t I have research to do?) Now, I’m thinking about MMOGs again, spurred on by a combination of hearing Christopher Klaus speak about Kaneva, and reading Pete Cashmore’s post about Multiverse. Kaneva and Multiverse are two players in an emerging business of providing MMOG hosting for the average Joe. In both cases, the hope is to bring innovative games to a new market of casual MMOG players by leveraging the creative power of you, me, and our friends sitting in a garage. Both companies will provide servers, a development platform, and a method of revenue sharing. And, both companies have good people behind them. Christopher Klaus formed ISS in 1994. The guys behind Multiverse (I keep trying to type Metaverse) are of Netscape fame. This will be interesting to watch.

The real question: is there a sufficient base of ambitious, amateur coders/modelers/artists/designers out there to make these companies work? I hope so, because I’d love to see innovative competition on the MMOG front. Other than having pretty graphics, graphical MMOGs don’t seem much different than good old MUDs. I’d like to see some new forms of interaction, and more interesting, intelligent ways to use the fact that thousands of people can share the same virtual environment. I’m also interested in non-entertainment uses of these spaces, such as MOOSECrossing.