Name: Indra Tanudjaja
Week 6T: Find three interesting topics in comdig.org 2000 Posted to website? YES.
I.
Video Game Images Persist Despite Amnesia (Science)
There seems to be increasing evidence that sleeping and dreaming are
important for learning because they are facilitating "unlearning" of
detailed information that is not relevant for the learning goals and that is
better forgotten in favor of task relevant information.
Stickgold et al. tested this hypothesis with subject who were asked to learn
the computer game tetris:
"People in both groups reported that, as they fell asleep, they dreamed
about images of blocks falling and rotating, as they do on the computer
screen when the game is in progress. They did not actually dream about the
game itself.
The amnesia patients did not remember playing the game and they did not ever
improve, unlike the volunteers with normal memory. Three of them did report
the strange dreams, however. "
"The researchers found that people who have just learned to play Tetris have
vivid images of the game pieces floating before their eyes as they fall
asleep, a phenomenon the researchers say is critical for building memories.
Much more surprisingly, the team also found that the images appear to people
with amnesia who have played the game--even though they have no recollection
of having done so."
II.
Sleep And Memory (New York Times)
This could be one of the embarrassing questions a little kid could ask the
parents or the teacher: "Why do we sleep?" When I was a kid one of the
answers was that we need to sleep so that we grow, and that's why little
kids need more sleep than adults who can stay up late to watch TV.
Other answers had to do with learning and memory and there seems to be
mounting evidence that there is a scientific basis for that sleep-memory
connection. It also would be consistent with the longer hours of sleep of
young children, since up to the age of about ten the number of neuronal
connections grows in the human brain, most rapidly in the first three years.
After that age some sort of pruning takes place and the neuronal connections
actually decrease in number.
Physiologically, (Hebbian) learning is explained as strengthening synaptic
connections between neurons that takes place every time these neurons are
active. But if that were the only process then it would not take too long
and our brain would be "full" like in the far-side cartoon. Therefore it is
also important that we learn to forget. Some theoretical arguments,
supported by artificial neuronal net simulations have suggested that sleep
might indeed the time when "un-learning" of all the irrelevant bits of
random information takes place that we are exposed to during our waking
hours.
Recent work by Stickgold et al. confirms again that learning and memory
(retention) is improved if one has a full night's sleep of more than six
hours. They studied the performance of volunteers to recognize and respond
to target patterns. It is interesting that their result seems to indicate
that a combination of deep sleep and rem sleep ("rapid eye movement" sleep,
during which most of the dreaming occurs) are required for an improved
memory and learning performance. On the other hand many higher mammals
(including dolphins) only sleep for brief periods at a time and there is
plenty of anecdotal evidence that many geniuses were notorious for their
short hours of sleep.
III.
Swarms of Robots Solve Complex Problems (Business Week Online)
Agent based modeling is an increasingly popular way of solving a number of
complex problems in different fields. Swarms of simulated agents follow
their local rules and interact with each others while searching for a
solution to a computational problems. Dedicated software environments like
the Swarm allow the user to use high level tools and libraries to set up the
simulations.
While all of these activities are happening in CyberSpace and the agents are
made of software only, researchers at Sandia National Laboratories in New
Mexico have implemented some of these artificial life ideas into hardware:
the agents are actually little robots that autonomously navigate in
difficult but real terrains and cooperate to solve real problems of military
and civilian applications. Among them are clearing of mine fields and other
operations in dangerous environments or for instance the search for victims
of avalanche accidents
The autonomy and communication among the robots would indicate a major step
forward in robotics applications that in the past depended on remote
operators that basically had to individually radio-control each robot. The
next generation robot would be smart enough to make for example many
navigational decisions only based on information about the goal, the current
location (determined by global positioning systems), the observed
environment and perhaps input from other robots in the swarm.