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VDIFF. Step A calculates the amount by which the rich have been made poorer, and uses this to make the
ogPrime's action selection aspect is fairly similar to MicroPsi (due to the common foundation in Dorner's Psi model), the dynamics are less similar. MicroPsi's dynamics are a little closer to being a formal neural net model, whereas ECAN's economic foundation tends to push it in different directions. The
s some simple simulated financial mechanisms, building on the economic metaphor of ELAN, that are different from, and more complex than, anything in MicroPsi. The main actors (apart from the usual ones like the AtomTable, economic attention alloca- tion, etc.) in the tale to be told here are as follows:
enough, in the sense that they lack sufficiently rich and nuanced interactions EFTA00623805 30 2 Wh
ion and intelligence. It has been tested on some practical control applications, and also on simulating artificial agents in a simple virtual world. MicroPsi's comprehen- siveness and basis in neuroscience and psychology are impressive, but in the current version of MicroPsi, learning and reasoning are ca
nts in a simple virtual world. MicroPsi's comprehen- siveness and basis in neuroscience and psychology are impressive, but in the current version of MicroPsi, learning and reasoning are carried out by algorithms that seem unlikely to scale. OCP incorporates the Psi model for motivation and emotion, so tha
enough, in the sense that they lack sufficiently rich and nuanced interactions HOUSE_OVERSIGHT_012945
tion and intelligence. It has been tested on some practical control applications, and also on simulating artificial agents in a simple virtual world. MicroPsi’s comprehen- siveness and basis in neuroscience and psychology are impressive, but in the current version of MicroPsi, learning and reasoning are car
ents in a simple virtual world. MicroPsi’s comprehen- siveness and basis in neuroscience and psychology are impressive, but in the current version of MicroPsi, learning and reasoning are carried out by algorithms that seem unlikely to scale. OCP incorporates the Psi model for motivation and emotion, so that
that is relatively simple, yet still intuitively rich and meaningful. Toward that end, the context of
e more attention. Action selection will be done via OpenPsi according to the Psi model, roughly similarly to how it is done in Joscha Bach's (2012) MicroPsi model. This means that actions will be chosen based on the probabilities with which they are estimated to lead to achievement of the currently high-
that is relatively simple, yet still intuitively rich and meaningful. Toward that end, the context of
e more attention. Action selection will be done via OpenPsi according to the Psi model, roughly similarly to how it is done in Joscha Bach's (2012) MicroPsi model. This means that actions will be chosen based on the probabilities with which they are estimated to lead to achievement of the currently high-
ine instances of matter into new ones in a fairly rich way: e.g. glue or tie solids togethermix liquids
ut on the big- picture level the main difference lies in the way the cognitive synergy principle is pursued in the two different approaches. Psi and MicroPsi rely on very simple learning algorithms that are closely tied to the "quad" neurosymbolic knowledge representation, and hence interoperate in a fai
ine instances of matter into new ones in a fairly rich way: e.g. glue or tie solids togethermix liquids
but on the big- picture level the main difference lies in the way the cognitive synergy principle is pursued in the two different approaches. Psi and MicroPsi rely on very simple learning algorithms that are closely tied to the “quad” neurosymbolic knowledge representation, and hence interoperate in a fairl
Entities connected to both Marc Rich and MicroPsi

Jeffrey Epstein
PERSONLeon Black
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Prince Andrew
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Alan Dershowitz
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George W. Bush
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Bill Clinton
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Prince Charles
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Stephen Hawking
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Jes Staley
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Wilbur Ross
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New York
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Jared Kushner
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Michael Douglas
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Joscha Bach
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Sergey Brin
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Hillary Clinton
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Vladimir Putin
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Bernie Sanders
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Earth
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