IBM simulates 530 billon neurons, 100 trillion synapses on supercomputer

Q-learning Q-learning is a model-free reinforcement learning technique. Specifically, Q-learning can be used to find an optimal action-selection policy for any given (finite) Markov decision process (MDP). It works by learning an action-value function that ultimately gives the expected utility of taking a given action in a given state and following the optimal policy thereafter. When such an action-value function is learned, the optimal policy can be constructed by simply selecting the action with the highest value in each state. One of the strengths of Q-learning is that it is able to compare the expected utility of the available actions without requiring a model of the environment. Additionally, Q-learning can handle problems with stochastic transitions and rewards, without requiring any adaptations. Algorithm[edit] The problem model, the MDP, consists of an agent, states S and a set of actions per state A. , the agent can move from state to state. where is the reward observed after performing in

Model Suggests Link between Intelligence and Entropy +Enlarge image A. Wissner-Gross/Harvard Univ. & MIT A. A pendulum that is free to swing through all angles in a plane can be stabilized in the inverted position by sliding the pivot horizontally, in the same way that you can balance a meter stick on your finger. The smallest disks, subjected to causal entropy forces, tend to work in a synchronized fashion to pull down the largest disk, in what the authors present as a primitive example of social cooperation. The second law of thermodynamics—the one that says entropy can only increase—dictates that a complex system always evolves toward greater disorderliness in the way internal components arrange themselves. Entropy measures the number of internal arrangements of a system that result in the same outward appearance. Hoping to firm up such notions, Wissner-Gross teamed up with Cameron Freer of the University of Hawaii at Manoa to propose a “causal path entropy.” –Don Monroe Don Monroe is a freelance science writer in Murray Hill, New Jersey.

Mathematicians help to unlock brain function Mathematicians from Queen Mary, University of London will bring researchers one-step closer to understanding how the structure of the brain relates to its function in two recently published studies. Publishing in Physical Review Letters the researchers from the Complex Networks group at Queen Mary's School of Mathematics describe how different areas in the brain can have an association despite a lack of direct interaction. The team, in collaboration with researchers in Barcelona, Pamplona and Paris, combined two different human brain networks - one that maps all the physical connections among brain areas known as the backbone network, and another that reports the activity of different regions as blood flow changes, known as the functional network. Lead author Vincenzo Nicosia, said "We don't fully understand how the human brain works. "The research is important as it's the first time that a sharp transition in the growth of a neural network has ever been observed," added Dr Nicosia.

Later Terminator: We’re Nowhere Near Artificial Brains | The Crux I can feel it in the air, so thick I can taste it. Can you? It’s the we’re-going-to-build-an-artificial-brain-at-any-moment feeling. It’s exuded into the atmosphere from news media plumes (“IBM Aims to Build Artificial Human Brain Within 10 Years”) and science-fiction movie fountains…and also from science research itself, including projects like Blue Brain and IBM’s SyNAPSE. Today, IBM (NYSE: IBM) researchers unveiled a new generation of experimental computer chips designed to emulate the brain’s abilities for perception, action and cognition. Now, I’m as romantic as the next scientist (as evidence, see my earlier post on science monk Carl Sagan), but even I carry around a jug of cold water for cases like this. The Worm in the Pass In the story about the Spartans at the Battle of Thermopylae, 300 soldiers prevent a million-man army from making their way through a narrow mountain pass. As they say, 300 is a tragedy; 300 billion is a statistic. Big-Brained Dummies Blurry Joints Instincts

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