Stories tagged artificial intelligence

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This video shows the evolution of coordinated behavior of simulated robot soccer players. In the simulation, each soccer player is controlled by a neural network. The neural networks are evolved using an evolutionary algorithm, so generation after generation the strategy improves.
The corresponding paper "Evolving neural network controllers for a team of self-organizing robots" is available at http://www.demesos.tk

Nov
23
2009

Reverse engineering the brain
Reverse engineering the brainCourtesy Thomas Schultz

Engineering computers that can think

Even simple brains, like those in a mouse, are amazing. A brain the size of a thimble that requires almost no energy, can navigate through mazes, survive in severe weather, or escape from a cat. Will we ever create a computer capable of such adaptable and creative "thinking"? One approach is to reverse engineer the brain of a mouse, rat, or cat.

Computer simulation achieves cat brain complexity

Dharmendra S. Modha is a team leader at IBM who is attempting to understand and build such a brain as cheaply as possible. Their latest achievement is a brain simulation with 1 billion spiking neurons and 10 trillion individual learning synapses.

Synapses are the key

Synapses are junctions between neurons and a key to how a brain learns. The strength of the chemical reactions within the synapses changes as the animal interacts with the environment These synaptic junctions are thought to encode our individual experience.

The problem with today's computers

Regular computer architecture has a separation between computation and memory.

“Surely there must be a less primitive way of making big changes in the store than by pushing vast numbers of words back and forth through the von Neumann bottleneck. Not only is this tube a literal bottleneck for the data traffic of a problem, but, more importantly, it is an intellectual bottleneck that has kept us tied to word-at-a-time thinking instead of encouraging us to think in terms of the larger conceptual units of the task at hand. Thus programming is basically planning and detailing the enormous traffic of words through the von Neumann bottleneck, and much of that traffic concerns not significant data itself, but where to find it.”

DARPA's SyNAPSE program

The goal of a DARPA program known as SyNAPSE (Systems of Neuromorphic Adaptive Plastic Scalable Electronics) is to create new electronics hardware and architecture that can understand, adapt and respond to a a changing environment.

What is cognitive computing?

Cognitive computing is the quest to engineer mind-like intelligent machines by reverse-engineering the computational function of the brain.

There is no definition or specification of the human mind. But, we understand it as a collection of processes of sensation, perception, action, cognition, emotion, and interaction. Yet, the mind seems to integrate sight, hearing, touch, taste, and smell effortlessly into a coherent whole, and to act in a context-dependent way in a changing, uncertain environment. The mind effortless creates categories of time, space, and object, and interrelationships between these.

Learn more about cognitive computing

Nov
21
2009

Robots that "think for themselves"

Fly's eyes: Can the nerves, eyes, and brain function of a fly be modeled within a computer circuit?
Fly's eyes: Can the nerves, eyes, and brain function of a fly be modeled within a computer circuit?Courtesy NeilsPhotography
Engineers are trying to design machines that can "think for themselves" when on surveillance or search and rescue missions. Somehow the machines has to look at its environment and decide what to do.
Have you ever tried to catch a fly? They are pretty good at seeing your hand and knowing just how to escape your grasp.

If we can figure out how a fly can do it ...

Can we figure out how a fly is able see, and find food, and escape from our fly swatters? With today's super microscopes, I am sure that we can visualize and model every nerve connection, muscle fiber, and eye facet.

Computational biology

David O’Carroll, a computational neuroscientist who studies insect vision at Australia’s University of Adelaide has been studying the optical flight circuits of flies, measuring their cell-by-cell activity. In a paper published in Public Library of Science Computational Biology, O’Carroll and fellow University of Adelaide biologist Russell Brinkworth describe an

algorithm composed of a series of five equations through which data from cameras can be run. Each equation represents tricks used by fly circuits to handle changing levels of brightness, contrast and motion, and their parameters constantly shift in response to input.

The "fly brain" circuits are small and use only a fraction of a milliwatt

“It’s amazing work,” said Sean Humbert, who builds miniaturized, autonomous flying robots,

“For traditional navigational sensing, you need lots of payload to do the computation. But the payload on these robots is very small — a gram, a couple of Tic Tacs. You’re not going to stuff dual-core processors into a couple Tic Tacs.

Learn more - mathematical modeling of insect biology

Secret Math of Fly Eyes Could Overhaul Robot Vision Wired Science
Robust Models for Optic Flow Coding in Natural Scenes Inspired by Insect Biology Computational Biology

We have constructed a full model for motion processing in the insect visual pathway incorporating known or suspected elements in as much detail as possible. We have found that it is only once all elements are present that the system performs robustly, with reduction or removal of elements dramatically limiting performance. The implementation of this new algorithm could provide a very useful and robust velocity estimator for artificial navigation systems.