Mind / Iron
by Bryan Bergeron, Editor ;
Bots and Intelligent Agents
I’m writing this editorial with the assistance of a
software robot or bot that I coded in AppleScript. This
particular bot completes words, suggests sentence
fragments, automates document formatting, and, in
general, supercharges Word. The bot is autonomous in
that it works in the background without my direct
supervision. My goal, however, is to create an intelligent
agent that can respond to my keyed or voice commands,
such as “Write a summary paragraph based on
information in Wikipedia/robots” and have the agent
obediently extract the information from the web,
construct sentences, and assemble the sentences into a
coherent paragraph that matches the style and level of
the other paragraphs in my editorial. No mean task.
The point in discussing bots and intelligent agents is
that I believe they are key to the success of socially
interactive mechanical robots. One obvious use for bots is
in automating the learning process. Bots and intelligent
agents can tirelessly comb through the Web in search of
patterns in data, perfecting searches of the Web on their
own. Wouldn’t it be great if your robot could learn new
words, phrases, and perhaps even objects by plugging
into the Web?
Another application of this technology in robotics is
communications. Chatter Bots, which have evolved
significantly since Eliza was introduced in the 1960s, can
form the basis of apparently intelligent dialogue between
6 SERVO 03.2010
robots and humans. Research has shown that the elderly
respond positively to the tactile and audible feedback
from soft and furry mechanical pets, such as the PARO
baby seal robot ( www.mahalo.com/paro-robot). I
strongly suspect that a social robot with more meaningful
dialog would be even more appreciated by elderly users.
In addition to generating content for text-to-speech
dialogues, Chatter Bots tied to video animation have
been developed to exhibit appropriate facial expressions
during voice recognition and speech synthesis. The
benefit of this technology to mechanical robotics is
obvious. Once you know the appropriate facial
expression, displaying that expression on an animatronic
face is relatively straightforward.
If you want to explore bots and intelligent agents, a
good place to start is with one of the open source
Chatter Bots. A relatively up-to-date website is AliceBot
( alicebot.blogspot.com) which features an online
Chatter Bot, as well as links to open source software. You
might want to explore the rules for the Loebner Prize
while you’re at it ( www.loebner.net). Each year, the
Cambridge Center for Behavioral Studies awards $3K and
a bronze medal for the most human-like computer. If you
want the grand prize — a gold medal and $100K — your
Chatter Bot will have to pass the Touring test. By the way,
if you manage to create a bot that’s indistinguishable
from a human, you can count on space in this magazine
for an interview.
Back to my relatively trivial AppleScript Bots ... you
can also gain insight into various means of training or
programming new behaviors in a mechanical robot by
working with simple scripting languages. If you use the
Unix OS, then you’re probably intimately familiar with
dozens of bots available for automating repetitive tasks.
As you’ll discover, scripting is good when you have a
known endpoint and fixed process to get there. Problems
arise in robotics when decisions aren’t clear cut, when
there are no specific rules that apply to a novel situation,
and when the process becomes non-deterministic. You
may ultimately have to rely on genetic algorithms, neural
networks, and various Bayesian techniques to create
something that can begin to pass the Touring test.
However, you can use simple scripting and script
generators to test your algorithms and overall approach
to adding interactive intelligence to your next robot
project. SV
