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Friday, July 08, 2005

Model Airplanes

I've been thinking about this all day. If the morning session of this first day of the Agent School had a byword, it'd be "situated." A close contender would be "embodied." It started with Jay Modi presenting one view of agents as being "situated AI," intelligence in a context. The thing that happens when a theorem prover meets a gripper or a video stream is wired into some neural network. Gal Kaminka continued the theme, presenting why robots aren't just agents, but agents in the hardest class of settings---dynamic, non-accessible, non-deterministic, and continuous environments. Afterward, Manuela Veloso upped the ante in her talk by vigorously proclaiming that "Only robots are agents!"

Later I was thinking about the fact that as a kid I was very into flying model airplanes. Large portions of my allowance were spent on balsa wood and glue, building ever fancier constructions. Eventually though I switched, focusing almost completely on programming. There were lots of reasons, but I have to admit that at least some part was that I got tired of all the tinkering and real world inconveniences. Mix the doping agent a little too heavy and your wings warp. Too thin and the covering fails. Be prepared to sand and sand until you get a piece shaped right. Then, once built, be prepared to spend hours trimming and adjusting your beauty until it flies just right, then watch in horror as a gust of wind takes it into a tree. Software just seemed so much cleaner, doing what you told it to do and only what you told it to do.

It was of course then karmic destiny that years later my first "real" job would be as a TA for an intro robotics course. I found myself spending untold hours regluing sensors torn from their LEGO mounts, calibrating finicky infrared distance sensors, and analyzing the slippage of different tire materials in our test arena. The gods were surely smiling as software betrayed me, presenting as much uncertainty and requiring as much trial and error and tinkering as my airplanes, or maybe more.

I, at least, find it hard (but not impossible) to argue Dr Veloso's stated point that robots are real agents, and "software agents" something less challenging. Interestingly, most counter-arguments that I can come up with or have heard seem to center on an agent that interacts with other agents or has some meaningful connection to the physical world, e.g. a sensor feed or even network access.

What I find less arguable though, is the closely related point that actually developing systems entails a great deal beyond theory and architectures. There's all that hacking, tinkering, caveats, and hard-earned special constants and thresholds that actually make things work well. Unfortunately, that often may be the bulk of the work but not receive much attention or accolades in its own right.

However, I think such efforts have their own rewards. Besides the accomplishment of seeing things actually working, I find that implementation in real settings---difficult, annoying, and time-consuming though it may be---often highlights new problems of interest. My lab does a lot of work with PDAs, tablets, and other small computing devices. In pretty much every way, developing with them is a terrible and frustrating experience. You haven't felt pain until you've had to use a stylus to peck away at reconfiguring an iPaq for a demo, or worried about repackaging code libraries to fit the space on a memory card. But, as my advisor claimed it would, actually trying things on them has on several occasions pointed out issues and opened up fascinating new areas to play around in.

Whether it requires robots or not to do so is perhaps arguable, but I think then that the notion put forth in the session of "agents" as real things situated in an environment and subject to its challenges and rigor, is an important notion with a large role in testing and developing the underlying science of AI...

(I confess though to still avoiding actual implementation like the plague; it seems a lot like real work)


Blogger Push Singh said...

Software agents are not less challenging than physical robot agents. AI researchers have not been able to build software agents that can understand even a children's story and answer questions about it, let alone make sense of your e-mail or an average web page.

Ask yourself this: In what ways is a person more than the type of robot AI researchers build today? The world is a complex place--people make use of a profound understanding of space, social relationships, minds, economics, artifacts, activities, goals, and many other such "common sense" realms to make sense of the world.

A serious problem with modern robotics research is that it barely touches on such issues.

8:29 AM  
Blogger Arthur said...

AI has been solved in theory and in software but a more serious problem is stopping the illegal American war against the people of Iraq and against the maimed and wasted American soldiers. Protest! Protest! Protest!

9:36 AM  
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