Archive for August, 2009

Scientific American Mind issue

August 28, 2009 Leave a comment

We plan on putting together a powerpoint highlighting some of the interesting pieces from this issue so we can review as a group next time we meet, but in the meantime if anyone would like to go purchase the article you can follow this link to do so.

Categories: News Stories

Color Qualia document from Brian Tsou

August 28, 2009 Leave a comment

Provided as a follow up to last week’s discussion on unique hues.

Color Qualia

Rats’ Mental Replay, from Maj. Eyster

August 28, 2009 Leave a comment

Found here,

Rats’ mental ‘instant replay’ drives next moves
August 26th, 2009 By Deborah Halber 
( — Researchers at MIT’s Picower Institute for Learning and Memory have found that rats use a mental instant replay of their actions to help them decide what to do next, shedding new light on how animals and humans learn and remember.
The work will appear in the Aug. 27 issue of the journal Neuron.
“By understanding how thoughts and memories are structured, we can gain insight into how they might be disrupted in diseases and disorders of memory and thought such as Alzheimer’s and schizophrenia,” said study author Matthew A. Wilson, the Sherman Fairchild Professor of Neuroscience at the Picower Institute. “This understanding may lead to new methods of diagnosis and treatment.”
Wilson’s laboratory explores how rats form and recall memories by recording — with an unprecedented level of accuracy — the activity of single neurons in the hippocampus while the animal is performing tasks, pausing between actions and sleeping. The hippocampus is the seahorse-shaped brain region researchers believe to be critical for learning and memory.
Wilson’s previous work has shown that after the animals run a maze, their brains “replay” during sleep the sequence of events they experienced while awake. Researchers believe this process is key to sleep-reinforced memory consolidation in both animals and humans.   We already knew this…

The latest study shows that these sequences also occur when the animals are awake and may help them decide what to do next.
Not-so-instant replay
When a rat moves through a maze, certain neurons called “place cells,” which respond to the animal’s physical environment, fire in patterns and sequences unique to different locations. By looking at the patterns of firing cells, researchers can tell which part of the maze the animal is running.
While the rat is awake but standing still in the maze, its neurons fire in the same pattern of activity that occurred while it was running. The mental replay of sequences of the animals’ experience occurs in both forward and reverse time order.

“This may be the rat equivalent of ‘thinking,’” Wilson said. “This thinking process looks very much like the reactivation of memory that we see during non-REM dream states, consisting of bursts of time-compressed memory sequences lasting a fraction of a second.
“So, thinking and dreaming may share the same memory reactivation mechanisms,” he said.
Memory’s building blocks  (This section may give us some insight into building an architecture)

“This study brings together concepts related to thought, memory and dreams that all potentially arise from a unified mechanism rooted in the hippocampus,” said co-author Fabian Kloosterman, senior postdoctoral associate.
The team’s results show that long experiences, which in reality could have taken tens of seconds or minutes, are replayed in only a fraction of a second. To do this, the brain links together smaller pieces to construct the memory of the long experience.
The researchers speculated that this strategy could help different areas of the brain share information — and deal with multiple memories that may share content — in a flexible and efficient way. “These results suggest that extended replay is composed of chains of shorter subsequences, which may reflect a strategy for the storage and flexible expression of memories of prolonged experience,” Wilson said.
Moreover, by comparing the content of the replay with the rat’s physical location on the track and his actual behavior immediately before and after the replay event the researchers could tell the rat was not just thinking about his most recent experience but also about other options, such as: “What if I turned around and went back the way I came?” or “How would I get here if my starting point is at a distant location?”
This suggests that the same brain mechanisms come into play to remember the past and consider future actions, reinforcing recent work by neuroscientists outside of MIT who determined that in humans, cognitive processes related to episodic recall and evaluation of future events overlap to a high degree.
Memory formation and future planning are among the cognitive functions ravaged by diseases such as Alzheimer’s disease, schizophrenia and psychosis.
“A better understanding of how we use memories, not only to learn from past experiences but also to explore our future options, can give us insights into how the system fails under these disease conditions,” Kloosterman said.
The MIT researchers plan to further explore the link between awake replay and cognition in animals engaged in more cognitively demanding tasks such as those involving multiple choices, where the rat has to make a decision (“do I go left or right?”) based on a prior learned rule.
In addition to Wilson, the study was led jointly by Kloosterman and MIT brain and cognitive sciences graduate student Thomas J. Davidson.
Provided by Massachusetts Institute of Technology

Categories: Uncategorized

Non-physics based representations CA ppt

August 28, 2009 Leave a comment

From Capt Amerika, a collection of recent thoughts addressing the difference between subjective and objective representations.

Note:  Updated to reflect changes that were projected at Aug 28th QUEST meeting.

Non physics based representations v2

Presentation from Dr. Carl

August 28, 2009 Leave a comment

Powerpoint that addresses what is unique in human minds when compared to animal minds.


Categories: Think Pieces

Simon says robot

August 28, 2009 Leave a comment

Andrea Thomaz, 33

Andrea Thomaz

Georgia Institute of Technology

Robots that learn new skills the way people do


Simon does: The robot Simon uses social cues to communicate whether it has understood what an instructor intended. Andrea Thomaz hopes that these abilities, in combination with computer vision, speech processing, and grasping capability, will enable Simon to operate successfully in the real world.
Credit: Yvonne Boyd

  Click here to see Simon in action.

Before robots can be truly useful in homes, schools, and hospitals, they must become capable of learning new skills. Andrea Thomaz, an assistant professor of interactive computing, wants them to learn from their users, so that experts don’t have to program every task. She aims to make robots that not only understand a human teacher’s verbal instructions and social signals but give social feedback of their own, using gestures, expressions, and other cues to let the person know whether they have correctly understood the directions.

Thomaz has designed machine learning algorithms based on human learning mechanisms and built them into her robots Junior and Simon, which have faces that make basic expressions and hands that can grasp simple objects. In experiments with people untrained in formal teaching, Junior has quickly learned enough about things in its environment to catch on to tasks such as opening and closing a box. –Kristina Grifantini

Categories: News Stories

Robots learn to lie

August 28, 2009 Leave a comment
Found in Popular Science

Evolving Robots Learn To Lie To Each Other

Wednesday, August 19, 2009

With the development of killer drones, it seems like everyone is worrying about killer robots. Now, as if that wasn’t bad enough, we need to start worrying about lying, cheating robots as well.

In an experiment run at the Laboratory of Intelligent Systems in the Ecole Polytechnique Fédérale of Lausanne, France, robots that were designed to cooperate in searching out a beneficial resource and avoiding a poisonous one learned to lie to each other in an attempt to hoard the resource. Picture a robo-Treasure of the Sierra Madre.

The experiment involved 1,000 robots divided into 10 different groups. Each robot had a sensor, a blue light, and its own 264-bit binary code “genome” that governed how it reacted to different stimuli. The first generation robots were programmed to turn the light on when they found the good resource, helping the other robots in the group find it.

The robots got higher marks for finding and sitting on the good resource, and negative points for hanging around the poisoned resource. The 200 highest-scoring genomes were then randomly “mated” and mutated to produce a new generation of programming. Within nine generations, the robots became excellent at finding the positive resource, and communicating with each other to direct other robots to the good resource.

However, there was a catch. A limited amount of access to the good resource meant that not every robot could benefit when it was found, and overcrowding could drive away the robot that originally found it.

After 500 generations, 60 percent of the robots had evolved to keep their light off when they found the good resource, hogging it all for themselves. Even more telling, a third of the robots evolved to actually look for the liars by developing an aversion to the light; the exact opposite of their original programming!

Categories: News Stories