Overall, Aachen’s not really all that different from anywhere else in the world, but it does have it’s differences from towns in the US, and I’m not just talking the language difference. One of the first things I noticed from the moment of getting onto the train was a different attitude toward alcohol. Some soccer fans got onto the train carrying beers and being generally rowdy as sport fans are. Later that day, I saw people having beers during lunch, and people walking down the street with beers. There’s no open container law here in Germany, and the attitude toward alcohol is generally relaxed.

But I sort of expected that difference coming into it, if by nothing other than stereotypes of typical Germans. There’s some other little differences that I didn’t really expect… door handles, for instance. I’ve taken a lot of notice in the way door handles are designed since my UI class. Nerdy, I know, but something as ubiquitous as a door handle needs to be designed well enough that anyone coming across it instantly knows how to interact with the door. The way door handles work in a lot of these buildings is backwards to my understanding. I often find myself coming to a door and pushing when I should pull or pulling when I should push. This isn’t helped by the fact that many doors open in where American convention would have them opening out.

Door handles aren’t the only difference in Aachen though, there’s also the great public transportation system. There’s 4 different bus routes I can use from my dorm room to get to various places in the city, and they all come about every 15 minutes. Then there’s the recycling–Germans are crazy about recycling. They have machines that will give you refunds for bottles, and they have 4 different separation bins for recyclables. On top of that, they also try to avoid creating trash in the first place, you can’t get plastic bags at the super market, for instance. You can get a reusable tote bag though.

The way these dorms are run is a bit different from what I’d consider the norm as well. There’s no toilet paper or hand soap kept in the bathrooms. You’ve got to bring your own. And the internet connection in the dorms is run by student volunteers, so you have to get a hold of those students whenever they decide to set their office hours.

Well, time to get ready for the day. I’ll be making another post again sometime soon. And hopefully this week I can find a USB cable to post some pictures.

Day two in Aachen went about as well and exhaustingly as day one. Class starts at 8:15, which means I have to get to the bus stop by 7:45, which means I have to be up by 7:00. Anyone who knows me knows that 7:00 is not typically an hour I would choose to wake up. To go to sleep? Maybe. But to get up for class? No.

After the 3 1/2 hours straight of German class, we were left with free time until 5. So I decided to wander around the center of town with a few of my classmates. We eventually found our way to a German bookstore, where I attempted to find the two books I’ve promised to obtain for friends back in the US – Die Undendliche Geschicte and a translated copy of Elfstones of Shanara. I managed to find some books by Terry Brooks, but only the latest ones. I couldn’t figure out where to find the Neverending Story.

From there, I spent the majority of time sitting around in a student cafe waiting for our program’s welcome meeting. This gave me a chance to meet Audrey and Ryan, two other participants in the UROP program.

The meeting was interesting. It was presented mostly by two professors who are actually from North America. Afterwards, we had the opportunity to meet with our advisors who will be working with us during the research part of the program, and also got to eat the well-known German food known as “pizza” (and apparently the worst pizza in Aachen by my advisor’s opinion). It’s okay it wasn’t actually a traditional German dish, seeing as I did have schnitzel for lunch (which was delicious, by the way).

The meeting concluded and a large group of us headed over to a bar, where we proceeded to do what one typically does at bars–drink beer and make friends. There’s an interesting smattering of students in this program. Majors range everywhere from Rhetoric to Psychology to Chemical Engineering, and home towns range from Costa Rica to Canada. Interestingly, the largest group of students from any school comes from Georgia Tech.

Unfortunately, I am still left without internet in my dorm. I shall be taking my laptop to class tomorrow to catch up with the world.

Tonight I write from Aachen, Germany. Of course, when I say tonight, I really mean this afternoon (in Atlanta time), but you get the idea. The trip here was incredibly long, but also incredibly uneventful.

It all started with the nine hour drive to Virginia, so that I could catch my flight from there to JFK. The hope was to spend an evening with family there, but unfortunately that evening went away as I delayed my trip with various last-minute tasks and a goodbye lunch with friends in Atlanta. After the long drive to Virginia, I arrived in time to get a 2 hour nap before having to wake back up and fly out of Norfolk.

After arriving in JFK I took a lot of time and just wandered around a bit. I had plenty of time, seeing as my Düsseldorf departure was 5 PM and I got in to JFK before 9 AM. More importantly, I had no idea which terminal to check into for my international flight, so I ended up visiting three different terminals (JFK apparently has before finding the terminal with Air Berlin.

After finding my terminal, there was a good deal of sitting and waiting, which gave me an opportunity to work on reading a good book. (Meeting at Corvallis, by SM Stirling – part of a great series) My flight did eventually board, after what seemed like years in my exhausted state, and then we were off to Germany.

Flying to Europe would have been the perfect time to catch up on that sleep I missed, unfortunately, I find it near impossible to get more than short two minute micronaps on planes. When my brain finally gets so exhausted it absolutely needs sleep, it’s generous enough to let me nod off, but once I get just that tiny bit of sleep on a plane, my brain will be like, “Okay, enough of that. Sitting up while sleeping sucks. Let’s wake up and wait for a real bed.” So my redeye flight was not any more restful than the night preceding it.

The flight was made even worse was the fact that the man sitting next to me was not big on respecting personal space, so his elbow and knees were consistently pushing on me.

After landing in Düsseldorf, I found customs to be much less of a hassle than I’d imagined it would be. I’d heard stories of bags being searched and the like, but all I had to do was flash my passport and get it stamped. There was also the medical form, with doctors making sure nobody was showing symptoms of Swine Flu before debarking, but that’s rather understandable.

After getting my bag, I found myself with the fun task of trying to catch a train in a country that I don’t speak the language. Luckily, I found that the ticketing system was all automated, with 6 languages to choose from. From there, all I had to do was hope I bought the right ticket and made the right connection, but it’s pretty hard to go wrong when the machine tells you which platforms to be on at which times. I found it slightly weird that during my entire ride nobody ever checked my ticket, but I imagine they check often enough it wouldn’t be worth the risk of not buying one.

Picking me up from the Westbahnhof was Felix, my Aachen buddy. He helped me find my dorm room and was even kind enough to buy me food so I’d have some, since most German stores are closed Sunday.

I settled down after getting to my dorm to take a nap, after which I met Felix so that we could walk around town a bit. We stopped to get some food at a restaurant, and then made our way to the local bar, where we had a few drinks and waited for Felix’s friend Christian, who is also a buddy in the UROP program and was bringing her along from the bahnhof.

All in all, it was a pretty good first day. Unfortunately, tomorrow begins at 7:00, and it’s currently 12. Time for some sleep.

Robots are cool.

Often, when one hears about AI, the topic of conversation is something grandiose. Strong AI, AI capable of conscious thought, is a fun thing to think about, but hardly something we can achieve currently, if at all. Discussions about this kind of AI are, more than anything, distractions from the equally interesting applications of AI that don’t require us to have a fully conscious machine.

For example, can we design a system that can adequately diagnose a mechanical problem, or a patient? Can we make a system capable of solving theorems or making logical deductions. These aren’t as exciting, but are certainly important to people working on AI, and are far more practical.

One of the first attempts at this was Cyc. Its goal is to be a sort of encyclopedia knowledge base capable of making inferences and answering queries. The database currently has over a million entries, and it’s been building since 1984. You can play around with it on their website, where they have a web frontend to query it. Interesting stuff. Of course, it still doesn’t know nearly enough. One suspects it might never be capable of learning enough.

The Turing Test is an interesting idea. The construction is as follows: you put a person in one room, a computer in another, and then have them communicating with a third person, whom we call the interrogator. The interrogator then asks questions of both and tries, with this information alone, to guess which is the computer and which is the man. The computer’s goal is to communicate with the interrogator so effectively as to convince him that it is the person.

Note that to be fair with the computer, our communication medium needs to be something like a chat room, something that separates physical perception from intellectual perception. Still, the test is weighted heavily in favor of the interrogator, since the computer must be capable of processing and using natural language in answers, and the interrogator has a 50-50 chance of guessing against the computer anyway.

Still, Turing was convinced in 50 years time that a computer would be capable of pulling off this feat… He said this in 1950. It’d seem Turing was off a little bit.

We all have an internal dialogue running in our heads all the time. It seems as though our very thoughts are tied to our linguistic ability. Given that this is the case, is it possible that these thoughts can ever be fully expressed in a language other than the one they are internally represented as? The linguistic relativity hypothesis, or Sapir-Whorf hypothesis, states that thought is so innately tied with language that there are thoughts in one language that are unique to that language and cannot be translated.

The Sapir-Whorf hypothesis has a weaker version that most scientists actually believe to be more accurate – that language impacts the thoughts and perceptions of people such that certain thoughts become more difficult to express in other languages, but not necessarily impossible. There are several studies that have been done about this.

Some of the more interesting ones include a study of people of different languages tasked to separate tokens into groups however they saw fit. Russians chose to separate light blue and dark blue into two separate groups, Setswana speakers would group green and blue. The theory is that these differences come from the differences in language. Setswana has no separate words for green and blue. Russian has two words for blue, one light and one dark. It doesn’t seem surprising to think language might have something to do with it.

I’ve taken several Japanese courses, and I’ve had friends ask me “how do I say X in Japanese?” Often, I just don’t know because I don’t have the vocabulary, but I’ve also seen that certain basic sentences just don’t really fit with any grammatical structures I’ve learned for Japanese. I guess that’s the linguistic relativity hypothesis at work.

Artificial neural networks are kinda nifty. To learn more about them, I thought I’d try playing with one. Here’s a couple of the places I tried: Blackjack with Reinforcement Learning and Java Mouse Neuron Test.

The first site uses an ANN to learn how to play Blackjack. You can start by playing alongside the computer in real time. The computer plays randomly at this point. If you want the computer to start playing better, the computer needs some alone time to get to learn the rules a little better. I set it to a 1000 learning episodes of 100 games each. As you run through the training you can watch the computers win average improving. It steadily goes from about 30%, which is about what you get playing randomly – to 40%. It then sits around 40% slowly improving. It’s impossible for the computer to really get above 50% since the game’s odds are weighted in favor of the dealer (the applet doesn’t account for pushes or splits).

It’s interesting how with just a few training episodes the computer can start really playing a better game. It’s hard to observe the overall difference playing as hands as slowly as a human needs to, but you can see the computer making more informed decisions after the training. ANNs are kind of nifty like that.

I decided to try to improve the training. I experimented with different values for winning and losing weights. Trying to find the right balance of reward/punishment to encourage learning in the quickest manner possible. I found weighting a win heavier than a loss was a quick way to favor learning, since losing is expected over 50% of the time any way. Weighting the wins too heavily did cause a lot more oscillation however, since the network started to think it understood what was going on just because of a chance win more often.

The other ANN I played with didn’t have any sort of training whatsoever. The associated paper discusses designing a neural net that learns more like a person and less like a computer with the hand of god involvement you’ll typically see. In the real world, there’s not someone to tell you every time whether you responded correctly or not, so the network was designed to learn in whichever way it desired, without a person telling it whether its actions were correct or not. I was able with a few tries to get the mouse to start to circle the goal without any sort of training whatsoever. I’d like to play around with this idea further – no training ANNs…

Artificial Life is an interesting concept. The idea is to make computer programs that model life in interesting ways and study them with the hopes of learning more about the process of evolution itself. For example, some A-Life programs start with a single creature programmed to learn about its environment and adapt. These creatures soon develop complex strategies that were not originally programmed. This is the case in the classic example of Animats.

The other possibility for A-Life programs is simulating entire ecosystems of artificial life. These I find more interesting, because they more often include genetic components and simulate natural selection. One such simulation is Noble Ape. I downloaded it and gave it a whirl. (Download Noble Ape Here.)

It includes all sorts of features, including weather simulation, random maps, senses for the simulated monkeys, etc. It even shows a simulation of their brain. The program even allows for scripting the monkeys to give them certain characteristics. All in all, it’s pretty fascinating watching the monkeys roam around trying to learn stuff.

The interface is kind of a pain to learn to use. The monkeys have several variables that define their overall behavior – including energy levels, fear, desire, along with location. These are presented in a sort of nonsensical array of gauges that don’t really make sense at first. It takes a little bit of practice, but it becomes easier to understand what is going on and you begin to see how their programming is really affecting their behavior.

A-Life doesn’t just focus on such complicated models though, it can also deal with simpler models. Lotus Artificial Life has some such examples. From the simple rules of the automata they have created, complex shapes and self replicating automata will form. This kind of study focuses more than the previously discussed examples on the effects of evolution.

One of our guest lecturers for Cog Sci in the past few weeks was a guy from a group at Georgia Tech investigating BCIs – Brain-Computer Interfaces. He had a very interesting topic to talk about – becoming cyborgs. There is a lot of interesting research being done in the area of interfacing computers with nervous systems. There are wheelchairs controlled by thought and robotic arms that respond to the same impulses our brain uses to control our real arms.

To me, one of the more interesting points of research pointed out by the lecture was the work of Kevin Warwick. He has had an array of electrodes implanted into his arm and used it to control, over the internet, an arm. Not only could he control it, but he was also able to receive stimulus from the arm, allowing him to control it blindfolded. His wife got an implant as well, and they set up bidirectional communication between the implants controlled by thought. (Read more about it in his paper: “Thought communication and control: a first step using radiotelegraphy”)

The result – a crude, but completely thought-driven means of communication. Kevin was able to send finger twitches to his wife, who would feel the twitches and could accurately identify them, and she could send back the same. This is a really cool idea to me. The ability to transmit thoughts, even if they are only simple twitches for now, is something that could be an extremely useful tool and lots of fun too.

What’s this mean for the average joe? Well, nothing for right now. But with all of the advances science has been making, bionic eyes, robotic arms, remote controlled rats… we could be seeing a future where people are as much machine as they are person. Being able to connect to the internet with a thought, being able to get a limb replaced with the full ability of the original arm… None of it seems quite as far fetched any more. Science has begun to understand the brain to the point where we can create technology that taps directly into it.