Herself’s Artificial Intelligence

“The DARPA System F6 is based on a concept whereby a group of spacecraft operate together wirelessly as a single unit to enable flexible data sharing and distributed processing that will allow cooperative communications among the spacecraft. This concept of multiple spacecraft operating together to perform a mission similar to that of a single larger spacecraft is known as ‘fractionation,’” Boeing said.

“We believe the fractionation spacecraft concept proposed by our team can be a game-changer that could provide the high degree of flexibility needed for responsive space missions,” said Bob Friend, director for Boeing Operationally Responsive Space.

“The objective of the DARPA System F6 is to demonstrate the feasibility and benefits of a satellite architecture wherein the functionality of a single spacecraft is replaced by a cluster of wirelessly interconnected spacecraft that could perform a wider variety of tasks than single systems. Along with potential increases in flexibility, this technology also may reduce overall program costs,” Boeing said. [ read more Boeing wins $12M DARPA F6 space contract]

‘Science’ published a paper by M.D.Cohen ‘Learning with Regret’ This paper is about an economic prediction system that lets the agents learn from past errors. Agents look back at previous decisions to see what better outcomes may have happened if they had chose differently. In doing so agents make better future decisions.

Not everyone feels regret is useful for economic agents. Yu-Han Chang argues that systems that minimize regret can perform better than ones using regret.

More information:
Micheal D Cohen
Center for Complex Systems

Papers:
Rational Competative analysis (pdf )
Recognizing the New: A Multi-Agent Model of Analogy in Strategic Decision Making ( pdf )
Rewarding Regret (pdf)
Diversity and Communication in Teams: Improving Problem Solving or Creating Confustion? (pdf)
Economics papers by Massimo Warglien

The Japanese are really going to make it much more fun to age. What is really cool is the technology for these glasses is well known and already available.

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Simply tell the glasses what you are looking for and it will play into your eye a video of the last few seconds you saw that item.

Built on to the glasses is a tiny camera which makes a constant record of everything the wearer sees: the tiny display inside the glasses identifies what is being scanned and a small readout instantly announces what the computer thinks the object probably is. For some things that look different from a range of angles, however, the glasses offer only a “best guess” – they are better at identifying a guitar and a chair than a coathanger or battery.
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The hardware itself is not extraordinary: what has taken Professor Kuniyoshi several years to perfect is the computer algorithm that allows the goggles to know immediately what they are seeing. It is, he says, a problem that has always vexed the fields of robotics and artificial intelligence.

But working in a team with Tatsuya Harada, one of Japan’s masters of the science of “fuzzy logic”, Mr Kuniyoshi believes he has cracked the problem. Behind the goggles is possibly the world’s most advanced object recognition software and a computer that can learn the identity of new objects within seconds.

So if the user wanders round the house for about an hour telling the goggles the name of everything from that coathanger to the kitchen sink, they will remember. Then if, at some point in the future, you ask them where you last saw a particular item, they will play the appropriate footage.

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[ read more The glasses that can help you find anything ]

See also:
Robots for old boomers (UMass project aims to assist aging population )